Dragonfly

Top 425 Databases Compared

Compare & Find the Perfect Database For Your Project.

Database Types:AllDistributedRelationalDocumentAnalytical
Query Languages:AllSQLNoSQLRESTSPARQL
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DatabaseStrengthsWeaknessesTypeVisitsGH
Redis Logo
  //  
2009
In-memory data store, High performance, Flexible data structures, Simple and powerful APILimited durability, Single-threaded structureIn-Memory, Key-Value70618267079
Prometheus Logo
  //  
2012
Powerful querying, Flexible, Robust alertingLimited long-term storage, Basic UITime Series23349355830
etcd Logo
  //  
2013
High availability, Consistent, ReliableLimited to key-value storage, Not suited for large datasetsKey-Value, Distributed1615447875
Meilisearch Logo
  //  
2019
Real-time search capabilities, Easy integration with various platformsLimited advanced query functionalities, Focus on text search primarilySearch Engine1679147474
Apache Spark Logo
  //  
2014
Fast processing, Scalability, Wide language supportMemory consumption, ComplexityAnalytical, Distributed, Streaming581620840021
ClickHouse Logo
  //  
2016
Fast queries, Efficient storage, Columnar storageLimited transaction support, Complex configurationAnalytical, Columnar, Distributed23335037761
TiDB Logo
  //  
2016
Horizontal scalability, Strong consistency, High availability, MySQL compatibilityComplex architecture, Relatively new community supportRelational, NewSQL, Distributed16352737307
LevelDB Logo
  //  
2011
High read/write performance, Simple and lightweight, Optimized for fast storageLimited to key-value storage, Not a relational database, No built-in replicationKey-Value, Embedded36595
Milvus Logo
  //  
2019
Open-source vector database, Efficient for similarity search, Supports large-scale dataLimited to specific use cases, Complexity in high-dimensional data handlingMachine Learning, Vector DBMS9065830810
CockroachDB Logo
  //  
2015
Distributed SQL, Strong consistency, High availability and reliabilityRelatively new technology, Complex to set upRelational, Distributed, NewSQL9612930151
InfluxDB Logo
  //  
2013
Optimized for time series data, High-performance writes and queriesLimited SQL support, Vertical scaling limitationsTime Series14775628986
RocksDB Logo
  //  
2013
High performance for write-heavy workloads, Optimized for fast storage environmentsComplex API, Lack of built-in replicationKey-Value, Embedded1285628675
SurrealDB Logo
  //  
2021
Highly scalable, Multi-model database, Supports SQLRelatively new in the market, Limited community supportDocument, Graph, Relational1245827544
RethinkDB Logo
  //  
2009
Real-time changes to query results, JSON document storageLimited active development, Not as popular as other NoSQL optionsDocument, Distributed277126781
MongoDB Logo
  //  
2009
Document-oriented, Scalable, Flexible schemaConsistency model, Memory usageDocument, NoSQL293707626383
Dragonfly Logo
  //  
2022
High throughput, Low latencyEarly stage, Limited documentationIn-Memory, Key-Value9971625936
DuckDB Logo
  //  
2018
Lightweight and fast, In-memory analyticsLimited scalability, Single-node onlyAnalytical, Columnar4028224416
Apache Flink Logo
  //  
2011
Highly scalable, Real-time data processing, Fault-tolerantComplexity in setup and management, Steeper learning curveStreaming, Distributed581620824136
TDengine Logo
  //  
2018
Time-series optimized, Lightweight and efficient, Built-in clusteringLimited support for complex queries, Smaller user communityTime Series, Distributed244923409
Typesense Logo
  //  
2018
Fast and Relevant Search, Easy to Use APILimited Scalability, Development CommunitySearch Engine2813421177
Qdrant Logo
  //  
2020
High-performance vector search, Easy to use, Open sourceRelatively new with limited ecosystem, Limited query capabilitiesVector DBMS2699320657
Dgraph Logo
  //  
2017
Graph-based data model, High throughput, Scalable architectureSteeper learning curve, Fewer integrationsGraph, Distributed2129320447
Vitess Logo
  //  
2011
Scalability, Efficiency with MySQL, Cloud-native, High availabilityComplex setup, Limited support for non-MySQL databasesDistributed, Relational1512718697
Dolt Logo
  //  
2019
Git-like version control for data, Facilitates collaboration and branchingRelatively new with limited adoption, Potential performance issues with very large datasetsRelational, Distributed3018817976
TimescaleDB Logo
  //  
2018
Excellent time-series support, Built on PostgreSQLRequires PostgreSQL knowledge, Limited features compared to specialized DBMSRelational, Time Series14633217911
Valkey Logo
  //  
2024
High availability, Low latency, Rich data structures, Open-source licensingEmerging community support, Developing documentationIn-Memory, Key-Value, Distributed1898917384
PouchDB Logo
  //  
2012
Offline capabilities, Synchronizes with CouchDB, JavaScript basedLimited scalability, Single-node architectureDocument, Embedded1598516909
PostgreSQL Logo
  //  
1996
Open-source, Extensible, Strong support for advanced queriesComplex configuration, Performance tuning can be complexRelational, Object-Oriented, Document154896816254
Presto Logo
  //  
2012
Distributed SQL query engine, Query across diverse data sourcesNot a full database solution, Requires configurationDistributed, Analytical3156816065
Chroma Logo
  //  
2022
Optimized for handling vector data, Real-time processing capabilitiesNew technology with a smaller community, Limited integrations compared to established systemsVector DBMS015488
QuestDB Logo
  //  
2019
High-performance for time-series data, SQL compatibility, Fast ingestionLimited ecosystem, Relatively newer databaseTime Series, Relational3253614626
FoundationDB Logo
  //  
2012
ACID transactions, Fault tolerance, ScalabilityLimited to key-value data model, Complex configurationDistributed, Key-Value739314550
Badger Logo
  //  
2017
High performance, Efficient key-value storage engineKey-value store specific limitations, Limited to embedded scenariosKey-Value, Embedded2129313990
ScyllaDB Logo
  //  
2015
Extremely fast, Compatible with Apache Cassandra, Low latencyLimited built-in query language, Requires managing infrastructureDistributed, Wide Column6935113604
ArangoDB Logo
  //  
2011
Multi-model capabilities, Flexible data modeling, High performanceComplexity in setup, Learning curve for AQLDistributed, Document, Graph1655113579
Memcached Logo
  //  
2003
High-performance, Distributed, Simple designNo persistence, No redundancy, Limited querying capabilitiesIn-Memory, Key-Value1360013561
Apache Druid Logo
  //  
2011
Sub-second OLAP queries, Real-time analytics, Scalable columnar storageComplexity in deployment and configurations, Learning curve for query optimizationAnalytical, Columnar, Distributed581620813522
Neo4j Logo
  //  
2007
Efficient for graph-based queries, Supports ACID transactions, Good visualization toolsNot suitable for very large datasets, Steep learning curve for complex queriesGraph29027713428
SQL.JS Logo
  //  
2013
Runs entirely in the browser, No server setup required, Supports SQL standardLimited storage capabilities, Dependent on browser resourcesRelational, Embedded72712795
Apache Doris Logo
  //  
2017
Highly scalable, Real-time analytics orientedRelatively new, Smaller communityAnalytical, Columnar581620812753
VictoriaMetrics Logo
  //  
2018
Time-series optimizations, Scalability, Open-sourceNarrow focus on time-series data, Limited community compared to PrometheusTime Series3024712443
Weaviate Logo
  //  
2018
Built-in machine learning, Vector-based similarity searchesLimited support for complex queries, Relatively new technologyVector DBMS7019811537
KeyDB Logo
  //  
2019
High-performance, Multi-threaded, Compatible with RedisRelatively new with a smaller community, Potential compatibility issues with Redis extensionsIn-Memory, Key-Value948311534
MySQL Logo
  //  
1995
Open-source, Wide adoption, ReliableLimited scalability for large data volumesRelational320237810889
NebulaGraph Logo
  //  
2019
High performance on graph data, Horizontal scalabilityRelatively new with a growing community, Complex to deploy and manage for beginnersGraph1082810837
Citus Logo
  //  
2011
Distributed SQL, Scalable PostgreSQL, Performance for big dataRequires PostgreSQL expertise, Complex query optimizationDistributed, Relational970410622
Trino Logo
  //  
2012
Highly scalable, Low latency query execution, Supports multiple data sourcesMemory intensive, Complex configurationDistributed, Analytical3574910480
Integration with Microsoft products, Business intelligence capabilitiesRuns best on Windows platforms, License costsRelational, In-Memory72317446210076
OpenSearch Logo
  //  
2021
Open source, Scalable, Real-time search and analyticsRelatively new, Less enterprise support compared to ElasticsearchSearch Engine, Distributed991099825
Manticore Search Logo
  //  
2017
High-performance full-text search, Real-time synchronization with SQL databases, Open-source and community-drivenLimited non-search capabilities, Smaller community compared to other search enginesSearch Engine50259055
YugabyteDB Logo
  //  
2017
High availability, Horizontal scalability, Open sourceRelatively new, less mature, Smaller community compared to older databasesDistributed, NewSQL376489016
StarRocks Logo
  //  
2020
Fast query performance, Unified data model, ScalabilityRelatively new softwareAnalytical, Relational, Distributed519029011
Apache Cassandra Logo
  //  
2008
High availability, Linear scalability, Fault tolerantComplexity of operation and maintenance, Limited query languageDistributed, Wide Column58162088870
Immudb Logo
  //  
2019
Immutable, Cryptographically verifiableRelatively new, Limited ecosystemBlockchain, Distributed, In-Memory17738635
LiteDB Logo
  //  
2016
Single-file database, Lightweight and fast, No SQL server requiredLimited to C# ecosystem, Not suitable for very large scale applicationsDocument, Embedded33758628
OceanBase Logo
  //  
2010
High availability, Strong consistency, Horizontal scalabilityComplex setup, Limited community supportDistributed, NewSQL829448430
BoltDB Logo
  //  
2013
Lightweight, EmbeddedLimited scalability, Single-reader limitationKey-Value, Embedded11204898300
Deep Lake Logo
  //  
2020
Optimized for AI and ML, Efficient data versioningComplexity in integration, Niche domain focusMachine Learning, Vector DBMS289448180
Databend Logo
  //  
2021
High-performance OLAP, Elastic scalabilityFeature maturity, Community sizeAnalytical, Distributed07868
RisingWave Logo
  //  
2021
Real-time analytics, ScalabilityNascent ecosystem, Limited user documentationStreaming, NewSQL344667058
AlaSQL Logo
  //  
2014
Lightweight and fast, Browser-based data processing, Flexible and SQL-likeNot suitable for large datasets, Limited to JavaScript environmentsIn-Memory7037
Lovefield Logo
  //  
2015
Client-side database, Supports SQL-like queries in JavaScript, Optimized for web applicationsLimited to client-side usage, No longer actively maintainedRelational, In-Memory6813
LokiJS Logo
  //  
2014
In-memory database, Lightweight, FastLimited scalability, No built-in persistenceIn-Memory06754
SQLite Logo
  //  
2000
Serverless, Lightweight, Broadly supportedLimited to single-user access, Not suitable for high write loadsRelational, Embedded4877226737
CouchDB Logo
  //  
2005
Easy replication, Schema-free JSON documents, High availabilityNot designed for complex queries, Slower than some NoSQL databasesDocument, Distributed58162086265
IBM Cloudant Logo
  //  
2014
Highly scalable, Managed cloud service, Fully integrated with IBM CloudLimited offline support, Smaller ecosystem compared to other NoSQL databasesDocument, Distributed133548696265
Hazelcast Logo
  //  
2008
Distributed in-memory data grid, High performance and availabilityComplex cluster management, Potential JVM memory limitsIn-Memory, Distributed491566160
Vespa Logo
  //  
2017
Scalable search and recommendation engine, Real-time data processing, Open sourceNiche market, Requires specialized knowledgeDistributed, Search Engine51245832
MariaDB Logo
  //  
2009
Open-source, MySQL compatibility, Robust community supportLesser enterprise adoption compared to MySQL, Feature differences with MySQLRelational1764455680
Apache IoTDB Logo
  //  
2018
Highly efficient for time series data, Supports complex analytics, Integrated with IoT ecosystemsLimited support for transactional workloads, Relatively new and evolvingTime Series58162085620
Apache Hive Logo
  //  
2010
Batch processing, Integration with Hadoop ecosystem, SQL-like queryingNot suited for real-time analytics, Higher latencyDistributed, Relational58162085556
Apache Pinot Logo
  //  
2014
Real-time analytics, High query performance, ScalableComplex setup, Relatively steep learning curveDistributed58162085518
JanusGraph Logo
  //  
2017
Scalable graph data storage, Open source, Supports a variety of backendsComplex setup, Requires integration with other tools for full functionalityGraph, Distributed16665331
EventStoreDB Logo
  //  
2012
Strong event sourcing features, Efficient stream processingRequires expertise in event-driven architectures, Limited traditional RDBMS supportEvent Stores, Streaming97625321
Apache HBase Logo
  //  
2008
Scalability, Strong consistency, Integrates with HadoopComplex configuration, Requires HadoopWide Column, Distributed58162085232
OpenTSDB Logo
  //  
2011
Scalable time series database, Strong community support, Highly optimized for large-scale dataComplex setup, Limited querying capabilities compared to SQL databasesTime Series10725002
MapDB Logo
  //  
2011
In-memory, Embedded storageLimited functionality, No built-in networkingEmbedded, In-Memory, Key-Value7704907
Apache Ignite Logo
  //  
2014
High-performance in-memory computing, Distributed systems support, SQL compatibility, ScalabilityComplex setup and configuration, Requires JVM environmentDistributed, In-Memory, Machine Learning58162084819
M3DB Logo
  //  
2016
Highly scalable, Optimized for time series data, High availabilitySteep learning curve, Complex setupTime Series, Distributed14769
OrientDB Logo
  //  
2010
Multi-model capabilities, Highly flexible schema support, Open-sourceComplex setup and maintenance, Performance can degrade with complex queriesGraph, Document26564752
Marqo Logo
  //  
2022
Focus on vector search, Real-time machine learning capabilities, Works well with structured and unstructured dataLimited features compared to more mature systems, Primarily focuses on search use casesSearch Engine, Vector DBMS, Machine Learning466104646
ObjectBox Logo
  //  
2017
High performance for embedded databases, Efficient object-oriented storageLimited cross-platform support, Smaller community compared to other DBMSEmbedded, Object-Oriented16034410
H2 Logo
  //  
2005
Lightweight, Embedded support, FastLimited scalability, In-memory by defaultRelational, Embedded616164216
CrateDB Logo
  //  
2014
Scalable distributed SQL database, Handles time-series data efficiently, Native full-text search capabilitiesLimited support for complex joins, Relatively new with possible growing painsDistributed, Relational, Time Series3044126
LedisDB Logo
  //  
2014
In-memory, Key-Value store, Simplified interfaceLimited to key-value use cases, Lacks advanced featuresKey-Value, In-Memory4103
BigchainDB Logo
  //  
2017
High throughput, Decentralized and immutable, Focus on blockchain technologyLimited querying capabilities, Not suitable for high-frequency updatesBlockchain, Distributed11674033
YDB Logo
  //  
2021
High scalability, Fault-tolerantRelatively new, Limited community supportDistributed, Relational67274015
TypeDB Logo
  //  
2016
Semantic modeling, Strong inference capabilitiesComplex set-up, Limited third-party integrationGraph, Document10833797
Apache Kylin Logo
  //  
2015
OLAP on Hadoop, Sub-second latency for big dataComplex setup and configuration, Depends on Hadoop ecosystemAnalytical, Distributed, Columnar58162083654
RavenDB Logo
  //  
2009
Easy to use with full ACID transaction support, Optimized for storing large volumes of documentsLimited ecosystem compared to more established databases, Smaller communityDocument, Distributed131373590
Tarantool Logo
  //  
2010
In-memory performance, Flexible data modelLimited ecosystem, Complex configurationIn-Memory, Distributed42993416
FlockDB Logo
  //  
2010
High throughput for relationship-based data, Optimized for social networking applicationsLimited functionality for complex queries, Not actively maintainedGraph, Distributed3337
TerminusDB Logo
  //  
2019
Graph database capabilities, Version control for data, RDF and JSON-LD supportLimited third-party integrations, Smaller community supportGraph, Document7862783
Project Voldemort Logo
  //  
2009
Scalability, Resilience to node failuresLimited support for complex queries, Not suitable for transactional dataKey-Value, Distributed2622640
LMDB Logo
  //  
2011
High performance, Memory mapped, ACID complianceLimited scalability, In-memory constraintsEmbedded, In-Memory, Key-Value9432589
XTDB Logo
  //  
2019
Temporal database capabilities, Flexible schemaRequires in-depth understanding for complex queries, Limited out-of-the-box analytics featuresDocument, Streaming5862574
Skytable Logo
  //  
2021
High performance, Scalable, Multi-modelRelatively new, Limited communityKey-Value, Distributed, In-Memory12440
GridDB Logo
  //  
2014
Time series data handling, High scalability, IoT optimizedLimited ecosystem, Less community supportTime Series, In-Memory, Key-Value59932381
GemFire Logo
  //  
2002
Low latency, Real-time data caching, Distributed in-memory data gridComplex setup, Enterprise pricingIn-Memory, Distributed33382852291
Geode Logo
  //  
2016
In-memory speed, High availability, Strong consistencyComplex setup, High memory usageIn-Memory, Distributed58162082291
Graph Engine Logo
  //  
2016
High-performance graph processing, Scalable, Supports distributed computingLimited adoption, Complex implementationGraph, Distributed, In-Memory7231744622206
Ehcache Logo
  //  
2003
Java-based, Easy integration, Robust CachingLimited to Java applications, Not a full-fledged databaseIn-Memory, Distributed59982017
TinkerGraph Logo
  //  
2012
Lightweight, Part of Apache TinkerPop framework, Graph traversal language supportLimited scalability, Not suited for large datasetsGraph58162081976
Apache Sedona Logo
  //  
2012
Geospatial data processing, ScalabilityComplex configuration, Requires integration with Apache SparkGeospatial, Distributed, Streaming58162081959
Apache Drill Logo
  //  
2015
Schema-free SQL, High performance for large datasets, Support for multiple data sourcesComplex configurations, Limited communityAnalytical, Distributed58162081948
YTsaurus Logo
  //  
2022
Scalability, Open-sourceComplex setup, Requires Kubernetes expertiseDistributed, Streaming14491885
Sphinx Logo
  //  
2001
Open-source, High-performance full-text searchRequires additional setup for some features, Less widely adopted than other search enginesSearch Engine215921807
MatrixOne Logo
  //  
2021
High performance, Scalability, Flexible architectureRelatively new, may have fewer community resourcesNewSQL, Distributed, Relational331788
PostGIS Logo
  //  
2001
Robust geospatial data support, Integrates with PostgreSQLComplexity in learning, Database size managementGeospatial, Relational824751751
KairosDB Logo
  //  
2012
Highly scalable, Optimized for time-series data, Open sourceLimited built-in analytics capabilities, Requires third-party tools for visualizationTime Series, Distributed1742
Elassandra Logo
  //  
2018
Combines Elasticsearch and Cassandra, Real-time search and analyticsComplex architecture, Requires deep technical knowledge to manageWide Column, Search Engine, Distributed01716
CnosDB Logo
  //  
2022
Time series focused, High throughputNew entrant in market, Limited community supportTime Series, Distributed17581666
OpenMLDB Logo
  //  
2020
Specifically designed for ML applications, High performanceNiche use case, Relatively new and evolvingAnalytical, Streaming16211594
NEventStore Logo
  //  
2010
Event sourcing, CQRS support, Modular designSteep learning curve, Limited to event sourcing use casesEvent Stores1580
Vald Logo
  //  
2020
Vector similarity search, ScalabilityYoung project, Limited documentationDistributed, Vector DBMS01538
CovenantSQL Logo
  //  
2018
Blockchain based, Decentralized, Secure data storage, Supports SQL queriesPerformance can be slower due to blockchain consensus, Limited ecosystem compared to traditional SQL databasesBlockchain, Distributed, SQL841496
EJDB Logo
  //  
2020
Lightweight, Embedded, Cross-platformLimited scalability, Single-threadedDocument, Embedded91446
GeoMesa Logo
  //  
2013
Scalable geospatial processing, Integrates with big data tools, Handles spatial and spatiotemporal dataComplex setup, Limited support for certain geospatial queriesGeospatial, Distributed5801433
Kuzu Logo
  //  
2020
Graph processing, Optimized for complex queries, Flexible data modelStill emerging, Limited documentationGraph20861413
Comdb2 Logo
  //  
2018
High performance, Distributed transactions, Designed for cloud environmentsLimited documentation, Smaller communityRelational1392
Elasticsearch Logo
  //  
2010
Full-text search, Scalability, Real-time analyticsComplex configuration, Resource-intensiveSearch Engine, Distributed10700701275
Firebird Logo
  //  
2000
Lightweight, Cross-platform, Strong SQL supportSmaller community, Fewer modern featuresRelational, Embedded485981260
Apache Solr Logo
  //  
2004
Full-text search capabilities, Highly scalable and distributed, Flexible and extensibleComplex configuration, Challenging to optimize for large datasetsSearch Engine58162081239
Infinispan Logo
  //  
2009
Highly scalable, Rich data structures, Supports in-memory cachingComplex configuration, Requires Java environment, Can be resource-intensiveIn-Memory, Distributed24111207
Enhanced performance, Increased security, Enterprise-grade featuresRequires tuning for optimal performance, Community supportRelational1469291157
Apache Impala Logo
  //  
2013
High-performance SQL queries, Designed for big data, Integration with Hadoop ecosystemLimited support for updates and deletes, Requires more manual configurationAnalytical, Distributed, In-Memory58162081152
Apache Jena Logo
  //  
2011
RDF and OWL support, Semantic web technologies integrationLimited to semantic web applications, Complex RDF and SPARQL setupRDF Stores, Graph58162081117
openGemini Logo
  //  
unknown
Open Source, Community DrivenLimited Features, Scalability ConcernsTime Series, Distributed01111
Aerospike Logo
  //  
2009
High performance, Low latency, Strong consistencyComplex setup, Limited secondary index capabilitiesKey-Value, Distributed161451087
Apache Accumulo Logo
  //  
2011
Strong consistency and scalability, Cell-level security, Highly configurableComplex setup and configuration, Steep learning curveDistributed, Wide Column58162081072
Apache Phoenix Logo
  //  
2014
SQL interface over HBase, Integrates with Hadoop ecosystem, High performanceHBase dependency, Limited SQL supportRelational, Wide Column58162081026
Realm Logo
  //  
2011
Mobile-focused, Object-oriented, Offline-firstNot a full SQL replacement, Limited support for complex queriesDocument, Embedded15781022
RRDtool Logo
  //  
1999
Efficient time series data storage, Compact data footprint, Good for monitoring dataLimited functionality compared to modern databases, Complex configuration for beginnersTime Series112671017
Tigris Logo
  //  
2022
Scalable, Multi-tenancy, Easy to use APIsRelatively new, Limited community supportDocument, Relational7136921
Blazegraph Logo
  //  
2006
Scalable graph database, Supports SPARQL queries, High-performance for RDF dataLimited support for complex analytics, Can be challenging to scale beyond certain limitsGraph, RDF Stores347898
Virtuoso Logo
  //  
1998
Supports multiple data models, Good RDF and SPARQL supportComplex setup, Performance variationRelational, RDF Stores12254867
Heroic Logo
  //  
2015
Time series data management, Scalability, Open-sourceNiche use case focus, Limited query language supportTime Series, Distributed0848
Xapian Logo
  //  
2000
Fast full-text search, Open source, Highly customizableComplex setup for beginners, Limited built-in scalabilitySearch Engine1276805
Apache HAWQ Logo
  //  
2013
SQL-on-Hadoop, High-performance, Seamless scalabilityComplex setup, Resource-heavyAnalytical, Relational5816208696
BaseX Logo
  //  
2005
Efficient XML data processing, Native XML database, XQuery processingNiche use case, Less mature compared to SQL databasesNative XML DBMS, Document2020693
ZODB Logo
  //  
1998
Object Persistence, Transparent Object StorageNot Suitable for Large Datasets, Limited ToolingObject-Oriented, Distributed106682
NCache Logo
  //  
2003
Scalability, Distributed caching, Focused on .NET applicationsPrimarily focused on Windows and .NET environmentsIn-Memory, Distributed7886650
Giraph Logo
  //  
2012
Highly scalable for graph processing, Integration with Hadoop ecosystemsRequires expertise in graph algorithms, Relatively complex setupGraph, Distributed5816208617
WhiteDB Logo
  //  
2011
In-memory database, Competitive read and write speedLimited persistence, No cloud offeringIn-Memory, Relational43608
ArcadeDB Logo
  //  
2021
Multi-model, Scalable, Easy integrationStill maturing, Limited third-party supportGraph, Document261499
Elliptics Logo
  //  
2009
Distributed, Fault-tolerant, Highly customizableComplex setup, Steep learning curveDistributed, Key-Value0497
BrightstarDB Logo
  //  
2011
RDF data model, Supports SPARQLNiche market, Limited adoptionRDF Stores, Graph0458
TomP2P Logo
  //  
2010
Peer-to-peer architecture, Scalability, DecentralizedComplex setup, Potential latency issuesDistributed, Key-Value0442
eXist-db Logo
  //  
2000
Native XML database, Supports XQuery and XPath, Schema-less approachLimited scalability compared to relational DBs, Complexity in managing large XML datasetsDocument, Native XML DBMS1557429
Oracle Coherence Logo
  //  
2001
Strong in-memory capabilities, High scalability and reliabilityComplex configuration, Higher cost of ownershipIn-Memory, Distributed15797952427
Warp 10 Logo
  //  
2014
High scalability for time series, Rich analytics featuresComplex data model, Steep learning curveTime Series, Distributed47388
MonetDB Logo
  //  
1993
High-performance analytic queries, Columnar storage, Excellent for data warehousingComplex scalability, Smaller community support compared to major RDBMSColumnar, Analytical2744383
RDF4J Logo
  //  
2004
Semantic Data Processing, Strong Community SupportSteep Learning Curve, Performance BottlenecksRDF Stores369365
Apache Derby Logo
  //  
2004
Lightweight, Pure Java implementation, EmbeddableLimited scalability, Not suitable for very large databasesRelational, Embedded5816208346
Fluree Logo
  //  
2018
Blockchain-backed storage and query, ACID transactions, Immutable and versioned dataRelatively new with a smaller user base, Performance can be impacted by complex queriesBlockchain, Graph, RDF Stores2170340
Apache Jackrabbit Logo
  //  
2004
Highly flexible, Scales well for content repositories, Java API supportComplex configuration, Limited performance in high-load scenariosContent Stores5816208335
Sequoiadb Logo
  //  
2011
High performance, Supports hybrid data models, Flexibility in deploymentLimited global presenceDocument, Search Engine7699326
4store Logo
  //  
2009
Optimized for RDF data, Scalable distributed databaseLimited query language support, Outdated documentationRDF Stores0291
Kyoto Tycoon Logo
  //  
2011
Lightweight, Fast key-value storageLimited query capabilities, Not natively distributedIn-Memory, Key-Value1672276
Hibari Logo
  //  
2010
Strong consistency, Highly reliableLimited adoption, Complex Erlang-based setupKey-Value, Distributed273
TigerGraph Logo
  //  
2012
Optimized for deep-link analytics, Highly scalable graph processingSteep learning curve, Relatively limited community supportGraph, Distributed9622269
Cubrid Logo
  //  
2008
Open-source, High availability, Optimized for web servicesLimited support outside of C, C++, and JavaRelational11110264
Hawkular Metrics Logo
  //  
2015
Time series data management, Integration with monitoring tools, ScalabilityPart of larger ecosystem, Specific to monitoring use casesTime Series, Distributed33234
ModeShape Logo
  //  
2009
Supports JCR API, Repository capabilitiesComplex setup, Steep learning curveHierarchical, Document, Content Stores164064217
HyperGraphDB Logo
  //  
2006
Represent complex relationships, Highly flexible modelNiche use cases, Lacks mainstream adoptionGraph, RDF Stores1215
Enterprise features, Security enhancements, Open source, Improved scalabilityDependent on MongoDB updates, Niche community supportDocument, Distributed146929212
ReductStore Logo
  //  
2021
Simplified time series data storage, Efficient data recall, Compact data formatsLimited to time-series data, Recently developedTime Series, Event Stores146177
Tkrzw Logo
  //  
2019
Lightweight, Versatile, Highly efficientLack of advanced features, Smaller community baseEmbedded, Key-Value1672177
EdgelessDB Logo
  //  
2020
Confidential computing, End-to-end encryption, High securityHigher overhead due to encryption, Potentially complex setup for non-security expertsDistributed, Relational2026170
Redland Logo
  //  
2000
Highly extensible, Supports various RDF formatsLimited scalability, Complex setupRDF Stores3157
Scalaris Logo
  //  
2008
Scalable key-value store, Reliability, High availabilityLimited to key-value operations, Smaller community supportDistributed, Key-Value0155
OrigoDB Logo
  //  
unknown
In-Memory Performance, Simple APILimited Scale for Large Deployments, Relativity NewIn-Memory, Document0137
Tajo Logo
  //  
2013
High performance, Extensible architecture, Supports SQL standardsLimited community support, Not widely adoptedAnalytical, Relational, Distributed5816208135
YottaDB Logo
  //  
2017
Robust transaction support, Open-sourceLimited to specific healthcare applications, Less community supportEmbedded, Hierarchical6376
NosDB Logo
  //  
2015
Scalability, NoSQL capabilitiesLimited ecosystem, Learning curve for new usersDocument, Distributed788644
Apache HugeGraph Logo
  //  
2018
Efficient graph processing capabilities, Supports large-scale graph traversal, Open-source and highly extensibleLimited documentation, Smaller community compared to other graph databasesGraph, RDF Stores9
DataFS Logo
  //  
2017
Versioned data storage, Metadata management, Data integrityNot optimized for high-speed transactions, Limited scalability compared to distributed databasesDistributed, Document06
Oracle Logo
1979
Robust performance, Comprehensive features, Strong securityHigh cost, ComplexityRelational, Document, In-Memory157979520
Scalable data warehousing, Separation of compute and storage, Fully managed serviceHigher cost for small data tasks, Vendor lock-inAnalytical10788670
ACID compliance, Multi-platform support, High availability featuresLegacy technology, Steep learning curveRelational133548690
Easy to use, Integration with Microsoft Office, Rapid application developmentLimited scalability, Windows-only platformRelational7231744620
Splunk Logo
2003
Powerful search and analysis, Real-time monitoring, ScalabilityCost, Complexity for new usersSearch Engine, Streaming7716500
Unified analytics, Collaboration, Scalable data processingComplexity, High cost for larger deploymentsAnalytical, Machine Learning12940130
Scalability, Integration with Microsoft ecosystem, Security features, High availabilityCost for high performance, Requires specific skill set for optimizationRelational, Distributed7231744620
Fully managed, High scalability, Event-driven architecture, Strong and eventual consistency optionsComplex pricing model, Query limitations compared to SQLDocument, Key-Value, Distributed7620968650
Serverless architecture, Fast, SQL-like queries, Integration with Google ecosystem, ScalabilityCost for large queries, Limited control over infrastructureColumnar, Distributed, Analytical64171768350
Ease of use, Rapid application development, Cross-platform compatibilityLimited scalability, Less flexibility for complex queriesRelational2796840
Real-time analytics, In-memory data processing, Supports mixed workloadsHigh cost, Complexity in setup and configurationRelational, In-Memory, Columnar69779620
Scalable data warehousing, High concurrency, Advanced analytics capabilitiesHigh cost, Complex data modelingRelational1328880
Strong transactional support, High performance for OLTP workloads, Comprehensive security featuresHigh total cost of ownership, Legacy platform that may not integrate well with modern toolsRelational69779620
Global distribution, Multi-model capabilities, High availabilityCan be costly, Complex pricing modelDocument, Graph, Key-Value, Columnar, Distributed7231744620
High performance, Flexibility with data models, Scalability, Strong mobile support with Couchbase LiteComplex setup for beginners, Lacks built-in analytics supportDocument, Key-Value, Distributed625770
High performance with OLTP workloads, Excellent support for time series data, Low administrative overheadSmaller community support compared to others, Perceived as outdated by some developersRelational, Time Series, Document133548690
High-performance data warehousing, Scalable architecture, Tight integration with AWS servicesCost can accumulate with large data sets, Latencies in certain analytical workloadsColumnar, Relational7620968650
Real-time synchronization, Offline capabilities, Integrates well with other Firebase productsNo native support for complex queries, Not suited for large datasetsDocument, Distributed64171768350
High performance for analytics, Columnar storage, ScalabilityComplex licensing, Limited support for transactional workloadsAnalytical, Columnar, Distributed194840
dBASE Logo
1980
Ease of use, Low resource requirementsLimited scalability, Older technologyRelational40200
High availability, Scalable, Fully managed by AWSTied to AWS ecosystem, Potentially higher costsRelational, Distributed7620968650
Kdb Logo
2000
High performance, Time-series data, Real-time analyticsSteep learning curve, Costly for large deploymentsTime Series, Analytical357670
Greenplum Logo
  //  
2005
Massively parallel processing, Scalable for big data, Open sourceComplex setup, Heavy resource useAnalytical, Relational, Distributed279090
High performance analytics, Simplicity of deploymentCost, Vendor lock-inAnalytical, Relational133548690
Seamless integration with Firebase, Realtime updates, ScalabilityCost can escalate, Limited querying capabilitiesDocument, Distributed64171768350
Fast search capabilities, Highly scalable, Easy integrationLimited to search use-cases, Pricing can be expensive for large-scale usageSearch Engine4290700
Strong OLAP capabilities, Robust data analyticsComplex implementation, Oracle licensing costsMultivalue DBMS, In-Memory157979520
Integrated AI capabilities, Part of Azure ecosystemDependency on Azure environment, Cost considerations for large data setsSearch Engine7231744620
Highly scalable, Advanced security features, Multi-modelHigher cost, Complex deploymentWide Column, Distributed5648030
Graphite Logo
  //  
2008
Efficient time series data storage, Easy integration with various toolsLacks advanced analytics features, Limited support for large data volumesTime Series9270
Enterprise-grade features, Strong data integration capabilities, Advanced security and data governanceHigh cost, Learning curve for developersDocument, Native XML DBMS93460
Fast analytics, Scalable, Operational and analytical workloadsHigh complexity for certain queries, Learning curve for database administratorsRelational, Columnar429590
Scalable NoSQL database, Fully managed, Integration with other Google Cloud servicesVendor lock-in, Complexity in querying complex relationshipsDocument, Distributed64171768350
Highly available, ScalableComplexity in setup, Not suitable for complex queriesKey-Value, Distributed22360
Small footprint, High performance, Strong security featuresLimited modern community support, Lacks some advanced features of larger databasesRelational, Embedded3573700
Scalable architecture, Comprehensive development tools, Multi-platform supportProprietary system, Complex licensing modelRelational3634350
Ingres Logo
1980
Enterprise-grade features, Robust security, High performanceLess community support compared to mainstream databases, Older technologyRelational825720
High performance, Auto-sharding, Integration with Oracle ecosystemComplex management, Oracle licensing costsDistributed, Document, Key-Value157979520
Embedded database capabilities, Reliable sync technology, Low resource usageLimited scalability compared to major databases, Slightly dated interfaceRelational, Embedded69779620
High availability, Massive scalability, Cost-effectiveLimited query capabilities, No complex queries or joinsDistributed, Key-Value7231744620
Specialized for vector search, High accuracy and performance, Easy integrationNiche use cases, Limited general database capabilitiesVector DBMS, Machine Learning1283150
HyperSQL Logo
  //  
2001
Lightweight, In-memory capability, Standards compliance with SQLLimited scalability for very large datasets, Limited feature set compared to larger RDBMSRelational, In-Memory25590
Real-time data analysis, Highly scalable, Integrated with Azure ecosystemComplex setup for new users, Azure dependencyAnalytical, Distributed, Streaming7231744620
Scalable NoSQL database, Real-time analytics, Managed service by Google CloudLimited to Google Cloud Platform, Complexity in schema designDistributed, Wide Column64171768350
Semantic graph database, Supports RDF and linked data, Strong querying with SPARQLLimited to graph-focused use cases, Complex RDF queriesRDF Stores, Graph394920
High performance, Integrated support for multiple data models, Strong interoperabilityComplex licensing, Steeper learning curve for new usersMultivalue DBMS, Distributed1203590
Memgraph Logo
  //  
2018
Focus on real-time graph processing, High performance with in-memory technologyLimited adoption compared to major graph databases, Smaller community supportGraph, In-Memory158580
Globally distributed with strong consistency, High availability and low latencyHigh cost, Limited control over infrastructureDistributed, Relational, NewSQL64171768350
High performance for time-series data, Powerful analytical capabilitiesNiche use case focuses primarily on time-series, Less widespread adoptionTime Series, Distributed6190
Adabas Logo
1969
High transaction throughput, Stability and maturityLegacy system, Less flexible compared to modern databasesHierarchical3068090
SAP IQ Logo
1994
High performance for analytical queries, Compression capabilities, Strong support for business intelligence toolsProprietary software, Complex setup and maintenanceColumnar, Relational69779620
Rapid application development, Scalable business applications, Python language support, Security enhancementsNiche use cases, Difficult to integrate with non-Multivalue systemsMultivalue DBMS1014060
Coveo Logo
2005
Advanced search capabilities, AI-powered relevanceProprietary platform, Complex pricing modelSearch Engine646920
High scalability, Supports multiple graph models, Fully managed by AWSAWS dependency, Complex pricing structure, Requires specific skill setGraph, RDF Stores7620968650
4D Logo
1984
Comprehensive development platform, Integrated with web and mobile solutions, Easy to use for non-developersLimited to small to medium applications, Less flexible compared to open-source solutions, Can be costly for large scaleRelational380270
MaxDB Logo
  //  
1987
Enterprise-grade stability, SAP integration, Handles large volumes of dataLesser known outside SAP ecosystem, Not as flexible as newer databases, Limited community supportRelational69779620
Oracle Berkeley DB Logo
  //  
1991
High performance, Supports multiple programming languages, EmbeddableLimited scalability, Complex to manage for large datasetsEmbedded, Key-Value157979520
Fully managed service, MongoDB compatibility, High availabilityVendor lock-in, Costly at scaleDocument, Distributed7620968650
Seamless integration with Apple ecosystems, Strong focus on privacy and security, Automatic synchronizationLimited to Apple platforms, Less flexible for non-Apple environmentsDocument, Key-Value4207779750
Highly scalable, Semantic reasoning capabilitiesComplex pricing model, Requires specialized knowledge for setupRDF Stores, Graph179670
Managed search-as-a-service, Scale automatically, Easy to integrate with other AWS servicesLimited customization compared to open-source alternatives, Costs can increase with large data setsSearch Engine7620968650
NoSQL data store, Fully managed, Flexible and scalableNot suitable for large performance-intensive workloads, Limited querying capabilitiesDistributed, Key-Value7620968650
Enterprise-grade support and features, Open-source based, High compatibility with OracleCan be complex to manage without expertise, More costly than standard open-source PostgreSQL for enterprise featuresRelational6397690
EXASOL Logo
2000
High-speed analytics, Columnar storage, In-memory processingExpensive licensing, Limited data type supportRelational, Analytical89670
Embedded database capabilities, Support for various platforms, Low footprintLimited awareness in the market, Older technology baseEmbedded00
IMS Logo
1968
High performance for OLTP, Reliable and matureLegacy system, Steep learning curveHierarchical133548690
SpatiaLite Logo
  //  
2008
Supports spatial data types, Lightweight and fully self-containedNot suitable for large-scale enterprise applications, Limited concurrencyRelational, Geospatial28020
Datomic Logo
  //  
2012
Immutable data, Temporal queriesLicense cost, Limited in-memory footprintDistributed, Document15770
High performance, Low-latency query execution, ScalabilityRelatively new, less community support, Focused primarily on analytical use casesAnalytical, Columnar382420
Fauna Logo
2015
Strong consistency, ACID transactions, Global distributionProprietary query language, Can be expensive at scaleNewSQL123840
Scalability, High performance, In-memory processingComplex learning curve, Requires extensive memory resourcesDistributed, In-Memory31290
Tibero Logo
2003
Oracle compatibility, High performanceLimited integration with non-Tibero ecosystems, Smaller market presence compared to leading RDBMSRelational186400
jBASE Logo
1991
Multivalue data model, Efficient for complex queryingOutdated technology stack, Limited developer communityMultivalue DBMS55340
VoltDB Logo
  //  
2010
High-speed transactions, In-memory processingMemory constraints, Complex setup for high availabilityDistributed, In-Memory, NewSQL360
High performance, Real-time analytics, GPU accelerationNiche market focus, Limited ecosystem compared to larger playersAnalytical, Distributed, In-Memory276310
Embedability, High performance, Low overheadLess known in the modern tech stack, Limited communityDocument, Key-Value825720
mSQL Logo
1994
Lightweight, Embedded systemsObsolete compared to current databases, Limited support and featuresRelational, Embedded2350
High performance in object-oriented data storage, Supports complex data modelsComplex setup, High license costObject-Oriented, Distributed00
Db4o Logo
  //  
2000
Lightweight, Object-Oriented databaseLimited support for distributed systems, Slower performance with complex queriesEmbedded, Object-Oriented00
In-memory, Real-time data processingRequires more RAM, Not suitable for large datasetsIn-Memory, Relational157979520
High scalability, Advanced analytics with embedded machine learningCost, Complex configurationRelational, Analytical133548690
D3 Logo
Unknown
N/AN/ADistributed, Document1014060
Optimized for time series data, Serverless and scalable, Built-in time series analyticsLimited to AWS ecosystem, Relatively new with less community supportTime Series7620968650
Mnesia Logo
1993
Integrates with Erlang/OTP, Supports complex data structures, Highly availableLimited to Erlang ecosystem, Not suitable for very large datasetsDistributed, Relational, In-Memory740900
GBase Logo
2004
Strong support for Chinese language data, Good for OLAP and OLTPLimited international adoption, Documentation primarily in ChineseRelational, Analytical158810
Supports data integration from various sources, User-friendly interface, Strong data preparation and analytics featuresPrimarily tailored for Hadoop ecosystems, Limited query flexibility compared to SQLAnalytical196760
openGauss Logo
  //  
2020
High Performance, Extensibility, Security FeaturesCommunity Still Growing, Limited Third-Party IntegrationsDistributed, Relational381700
HFSQL Logo
2005
Embedded Database Capabilities, Ease of UseLimited to PC SOFT Environment, Less Market Presence Compared to Mainstream DBMSEmbedded, Relational519430
Low Maintenance, Integrated FeaturesAging Technology, Limited AdoptionRelational, Embedded960
Rapid Application Development, User-Friendly InterfaceOutdated Technologies, Limited Community SupportRelational, Document10
High Stability, Excellent Performance on Digital EquipmentNiche Market, High Cost of OperationRelational157979520
Fully managed, Highly scalable, Compatible with Apache CassandraVendor lock-in, Higher cost at scaleWide Column7620968650
PlanetScale Logo
  //  
2018
Serverless, MySQL compatible, Highly scalableSchema changes can be complex, Relatively new to broader marketNewSQL, Distributed1090820
Real-time analytics, Built-in connectors, SQL-poweredCan be costly, Limited to analytical workloadsAnalytical, Distributed, Document76150
GT.M Logo
1977
High concurrency, Proven technology, Large user base in healthcareLimited support for modern APIs, Steep learning curveHierarchical00
Fast in-memory processing, Suitable for embedded systems, Supports real-time applicationsMay not be ideal for large disk-based storage requirementsIn-Memory, Embedded19970
In-memory speed, Scalability, Real-time processingCost, Requires proper tuning for optimizationIn-Memory, Distributed72380
High availability, Fault tolerance, ScalabilityLegacy system complexities, High costRelational, Distributed29018150
High availability, Strong consistency, ScalabilityVendor lock-in, Limited third-party supportRelational, Distributed131173210
Cost-effective, Compatible with MySQL, High performanceComplex pricing modelRelational, Distributed12982860
Advanced analytical capabilities, Designed for big data, High concurrencyCost can increase with scaleAnalytical, Relational12982860
Massive data processing capabilities, Integrated with Alibaba Cloud ecosystem, Cost-effectiveSteep learning curve for newcomersAnalytical, Distributed12982860
High compression rates, Fast query performance, Optimized for read-heavy workloadsLimited write performance, Legacy software with reduced community supportAnalytical, Columnar00
IDMS Logo
1973
Proven reliability, Strong transaction management for hierarchical dataComplex to manage and maintain, Legacy system with limited modern featuresHierarchical25058290
Hybrid architecture supporting in-memory and disk storage, Real-time transaction processingLimited global market penetration, Requires specialized knowledge for optimal deploymentRelational, In-Memory8330
NuoDB Logo
2010
Supports distributed SQL databases, Elastic scale-out with ACID complianceNot suitable for write-heavy workloads, Complex configuration for optimal performanceDistributed, NewSQL, Relational10
Scalability, High Performance, Integrated Data StoreComplexity, CostDistributed, Key-Value, Document, Time Series29018150
Sedna Logo
  //  
2019
Efficient XML Data Processing, Open SourceLimited Adoption, Niche Use CaseEmbedded, Machine Learning00
High performance, Scalable architecture, Supports complex queriesLimited managed cloud options, Proprietary solutionAnalytical, Relational, Distributed59900
High-performance data analysis, PostgreSQL compatibility, Seamless integration with Alibaba Cloud servicesVendor lock-in, Limited to Alibaba Cloud environmentAnalytical, Relational, Distributed12982860
High-performance analytics, Columnar storage, In-memory processing capabilitiesComplex licensing, Steep learning curveColumnar, Analytical825720
SciDB Logo
2011
Array-based data storage, Suitable for scientific data, Strong data integrity featuresNiche market focus, Limited adoptionAnalytical, Distributed5140
Proven reliability, Strong ACID complianceLegacy system, Limited modern featuresRelational, Hierarchical25058290
DBISAM Logo
1998
Embedded database, Small footprint, Easy integrationLimited scalability, Not open-sourceRelational, Embedded4940
High performance, Scalable, Handles complex interrelationshipsSteep learning curve, Limited community supportObject-Oriented, Graph3820
Handles large-scale data, Accelerates query performanceResource-intensive, Complex tuning requiredAnalytical, Columnar, Relational97970
High-speed in-memory processing, ACID compliance, Embedded database optionsProprietary technology, Limited community supportIn-Memory, Relational133548690
High-volume data analysis, Cloud-native platform, Integrated analyticsComplex pricing models, Steep learning curveAnalytical, Columnar30830
Cross-platform support, High reliability, Full SQL implementationLower popularity, Limited recent updatesRelational240
High-performance for Java applications, Object-oriented, Easy to use APILimited query language support, Not suitable for non-Java environmentsObject-Oriented37470
High reliability, Strong support for business applicationsOlder technology stack, May not integrate easily with modern systemsHierarchical, Relational6310
R:BASE Logo
1981
Established user base, Stable for legacy systemsOutdated technology, Limited community supportRelational00
HarperDB Logo
  //  
2017
Schema flexibility, High performance for mixed workloads, Easy deploymentRelatively new in the market, Limited enterprise adoptionDistributed, Document29480
High-performance, Embedded database, SQL supportLack of widespread adoption, Limited cloud supportEmbedded, Relational38990
HTAP capabilities, Machine LearningComplex setup, Limited community supportAnalytical, Distributed, Relational3810
In-memory data grid, High scalability, Transactional supportComplex setup, Vendor lock-inDistributed, In-Memory, Key-Value133548690
Object-oriented database, Transaction consistency, Scalable architectureComplex learning curve, Limited communityObject-Oriented, In-Memory840
High compatibility with Oracle, Robust security features, Strong transaction processingLimited global awareness, Smaller community supportRelational873800
Fast OLAP queries, Easy integration with big data ecosystemsComplex setup, Dependency on Hadoop ecosystemAnalytical, In-Memory85940
Embedded database solution, Easy integration with .NET applicationsLimited scalability, Windows platform dependencyRelational, Embedded00
High performance for embedded systems, Real-time data processingNiche use case focus, Smaller developer communityRelational, Embedded8990
atoti Logo
2020
High performance for OLAP analyses, Integrated with Python, Interactive data visualizationRelatively new in the market, Limited community supportAnalytical17470
GPU-accelerated, Real-time streaming data processing, Geospatial capabilitiesHigher cost, Requires specific hardware for optimal performanceIn-Memory, Distributed, Geospatial43560
Perst Logo
2005
Embedded and lightweight, Java and C# support, Small footprintLimited scalability, Not suitable for large applicationsObject-Oriented, Embedded19970
Scalable log processing, Real-time analytics, Easy integration with other Alibaba Cloud servicesRegion-specific services, Vendor lock-inAnalytical, Streaming12982860
Postgres-XL Logo
  //  
2014
Scalability, PostgreSQL compatibility, High availabilityComplex setup, Limited community support compared to PostgreSQLDistributed, Relational1330
Rasdaman Logo
  //  
1998
Geospatial data strength, Massive array data supportNiche application focus, Limited general-purpose database featuresGeospatial490
Database traffic management, Load balancingNot a database itself but a proxy, Complex deploymentRelational, NewSQL00
MultiValue flexibility, Backward compatibilityLegacy system, Limited modern supportMultivalue DBMS1870
ITTIA Logo
2007
Embedded use, Power efficiency, Targeted at IoTLimited to embedded systemsEmbedded, In-Memory00
undefined Logo
N/AN/A0
Strabon Logo
  //  
2012
Geospatial capabilities, Semantic web supportCan be complex to set up, Niche use casesRDF Stores, Geospatial11334560
High performance, In-memory database technology, Integration capabilitiesLimited market presence, Niche use casesIn-Memory, Relational00
Cloud-native architecture, ScalabilityNew to market, Limited documentationNewSQL, Distributed00
Scalable transactions, Hybrid transactional/analytical processingLimited adoption, Complex setupNewSQL, Distributed, Relational00
Scalability, High-performance graph queriesComplex setup, Limited community supportGraph, Distributed330
Global distribution, Low latencySize limitations, Eventual consistencyKey-Value, Distributed292727930
Full-text search, Easy setupFeature limitations, Scaling challengesSearch Engine, Document100970
Scalable, High performance for analytical queriesLimited documentation, Complex configurationTime Series, Distributed556440
OpenQM Logo
2004
MultiValue DBMS capabilities, Cost-effectiveNiche market, Smaller communityMultivalue DBMS00
GPU acceleration, Real-time analyticsHigh hardware cost, Complex integrationAnalytical, Relational2340
RDFox Logo
2015
Highly performant RDF store, Supports complex reasoningComplex to implement, Limited to RDFRDF Stores, Graph23100
Scalable time series data storage, High performance for big data analysis, Seamless integration with Alibaba Cloud ecosystemLimited adoption outside of Alibaba Cloud ecosystem, Less community support compared to open-source alternativesTime Series12982860
Enterprise-grade security features, Enhanced performance and scalability, Advanced analytics and data visualizationHigher cost for enterprise features, Limited community-driven developmentsRelational17907220
Massively parallel processing, High-performance graph analyticsComplexity in setup, Limited community supportGraph, RDF Stores, Analytical53590
FeatureBase Logo
  //  
2019
High-performance real-time analytics, Efficient data ingestionLimited to a specific use case, Steep learning curve for new usersColumnar, Distributed222990
Designed for continuous aggregation, Integrates with PostgreSQLLimited to streaming workloads, Small community sizeRelational, Streaming, Time Series00
High concurrency, Embedded supportLimited community, Less popular compared to other relational databasesRelational12030
Optimized for object-oriented applications, Flexible schema designNiche use case, Less adoption outside specific industriesEmbedded, Object-Oriented825720
Scalable, High availability, Flexible data modelLimited language support, Complex setup for beginnersKey-Value, Wide Column, Time Series12982860
Time Series optimized, Powerful analytics toolsNiche use cases, Steep learning curveTime Series, Geospatial880
RedStore Logo
Unknown
Lightweight RDF storeLimited capabilities, Sparse documentationRDF Stores, Graph326000
Hybrid data model, Proven reliabilityCostly licensing, Complex deploymentDocument, Relational, Embedded48020
High-speed data processing, Seamless integration with Apache Spark, In-memory processingRequires technical expertise to manageDistributed, In-Memory, Relational1556360
Real-time event storage and analytics, Integration with IBM Cloud servicesLimited third-party integrations, IBM Cloud dependencyEvent Stores, In-Memory, Relational133548690
Multi-model database supporting SQL and graphs, Combines relational and graph processingSolid understanding of SQL and graph databases required, Smaller community supportGraph, Relational00
High availability, Geographically distributed architectureLimited market penetration, Complex setupDistributed, Relational00
Strong data security, High performanceProprietary system, CostRelational, Embedded825720
Speedb Logo
2021
High-speed operations, NoSQL capabilitiesRelatively new, Limited ecosystemEmbedded, Key-Value580
Cross-platform, Integration with Valentina StudioNiche market, Limited public documentationRelational, Document94070
Scalable, Designed for time series data, High availabilityComplex setup, Limited query language supportTime Series, Key-Value22360
SQL support on Hadoop, Scalable, Robust queryingComplex to manage, Requires Hadoop expertiseRelational, Distributed880
MPP (Massively Parallel Processing) capabilities, High-performance analyticsProprietary technology, Niche use casesAnalytical, Distributed, Relational2930
Small footprint, Embedded database capabilitiesLimited scalability, Less popular than major DBMS optionsEmbedded, Relational4940
Jade Logo
1978
Integrated development environment, Object-oriented databaseOlder technology, Limited to Jade platformObject-Oriented, Document8060
Real-time analytics, In-memory processingProprietary technology, Limited third-party integrationsAnalytical, Columnar00
High-speed data ingestion, Time series analysisComplex setup, CostDistributed, In-Memory, Time Series00
Simplicity, Key-value storeLimited feature set, Not suitable for large-scale applicationsDocument, Key-Value00
Ultipa Logo
2018
Real-time graph processing, Advanced graph algorithmsSpecialized use case, ComplexityGraph4260
GreptimeDB Logo
  //  
2020
High performance, Scalable time-series storageRelatively new ecosystemDistributed, Time Series19030
Fast key-value storage, Simple APILimited feature set, No managed cloud offeringKey-Value10970
High performance for graph data, Good data compressionLimited community supportGraph00
Flexible architecture, Supports federationLimited maturity, Limited documentationDocument, Distributed17350
Optimized for complex queries, Highly scalableComplex setupGraph00
CubicWeb Logo
  //  
2008
Semantic web functionalities, Flexible data modeling, Strong community supportComplex learning curve, Limited commercial supportRDF Stores00
High-performance RDF store, Scalable triple storeLimited active development, Smaller communityRDF Stores00
AntDB Logo
2010
High concurrency, ScalabilityLimited international adoption, Complexity in setupDistributed, Relational00
Bangdb Logo
2013
High performance, Supports AI and machine learningLimited community support, Less known compared to mainstream databasesKey-Value, Document40700
Robust search capabilities, Fault-tolerantHigh initial cost, Complex setupSearch Engine, Content Stores330
Distributed in-memory data grid, Real-time analyticsLimited integrations, Licensing costsIn-Memory, Distributed18960
SiteWhere Logo
  //  
2015
Open-source IoT platform, Flexible and scalableComplex setup for new users, Requires integration expertiseDistributed200
chDB Logo
2023
High performance, Scalability, Efficiency in analytical queriesLimited user community, Relatively new in the marketColumnar, Analytical0
Highly scalable, Optimized for OLAP workloadsLimited ecosystem, Niche focusAnalytical, Columnar00
Proven reliability, ACID compliantProprietary, Lacks modern featuresRelational1150
Unified platform, JavaScript supportLimited community support, Niche use casesDocument, In-Memory0
High-performance analytics, Good for large data setsComplex setup, Steep learning curveAnalytical, Columnar, Distributed2700
STSdb Logo
2010
In-memory performance, LightweightLimited compared to full-featured DBMS, No cloud offeringIn-Memory, Key-Value976200
Performance, Supports ACID transactionsLimited adoption, Niche marketIn-Memory, Relational, Distributed00
High performance, Scalability, Integration with big data ecosystemsLess known in Western markets, Limited community resourcesAnalytical, Distributed, Relational00
Real-time data processing, Compatibility with multiple data formatsComplex setup, Smaller user communityDistributed, Relational00
Efficiency in edge computing, Data synchronizationNewer product with less maturity, Limited ecosystemEmbedded, Relational, Document48020
Lightweight, Java integrationLimited scalability, Fewer features compared to major SQL databasesRelational00
SparkleDB Logo
Unknown
N/AN/AGraph, RDF Stores00
gStore Logo
Unknown
N/AN/AGraph, RDF Stores2510
N/AN/AIn-Memory, Key-Value24580
Acebase Logo
Unknown
N/AN/ADocument, NoSQL0
SWC-DB Logo
Unknown
N/AN/AWide Column, Distributed00
Dydra Logo
2010
RDF data storage, SPARQL query execution, Managed cloud serviceSpecialized use, Limited broader use outside RDFGraph, RDF Stores1540
Object-oriented structure, Fast prototyping, Flexible data storageLess common compared to relational DBs, Specialized nicheObject-Oriented, Embedded00
N/AN/ADocument, Search Engine1560
Siaqodb Logo
  //  
2009
Embedded, Cross-platform, LightweightLimited query capabilities, Smaller community supportEmbedded, Object-Oriented00
High performance, Compression, ScalabilityProprietary, License costAnalytical, Relational00
SwayDB Logo
  //  
2018
Highly scalable, Simplified design, Immutable structureLimited ecosystem, Niche user baseKey-Value, Embedded00
Distributed, Scalability, Fault toleranceLimited community support, Complex setupDistributed, Relational00
BergDB Logo
Unknown
N/AN/AIn-Memory, Distributed00
Cachelot.io Logo
  //  
2016
High performance, In-memory key-value storageLimited feature set, Primarily for cachingIn-Memory, Key-Value1440
Graph-based, Schema-lessEmerging technology, Limited documentationDocument, Distributed00
Optimized for hybrid workloads, High concurrency, ScalableLimited adoption and community support, May require significant tuning for specific use casesGraph, Distributed00
Optimized for edge computing, Low latency processing, Real-time analyticsLimited support for complex query languages, May require specialized hardwareDistributed, Machine Learning890
Supports large-scale graph data, High performance, Flexible schemaLimited community support, Less mature compared to established graph databasesGraph, Analytical00
H2GIS Logo
2015
Integration with Spatial features, Open-sourceLimited support for non-spatial queries, Small communityGeospatial, Relational4160
Helium Logo
2019
Highly efficient, Immutable storageLimited query options, Niche use casesIn-Memory, Document, Distributed880
Flexible graph model, Compatibility with HadoopComplex setup, Limited documentationGraph, Distributed0
High write throughput, Efficient storage managementNot suitable for complex queries, Limited built-in analyticsKey-Value, Embedded0
iBoxDB Logo
2013
Embedded design, Ease of integrationLimited scalability, Small community supportDocument, Embedded1630
High performance, Scalable architectureProprietary system, Limited documentationEmbedded, Hierarchical00
JasDB Logo
  //  
2012
Flexible data model, JSON supportLimited commercial support, Basic querying capabilitiesDocument, Embedded00
K-DB Logo
Unknown
High-speed columnar processing, Strong for financial applicationsLimited general-purpose usage, Specialized use caseTime Series, In-Memory1248200
Linter Logo
1995
Strong SQL compatibility, ACID complianceNiche market focus, Legacy systemRelational16050
Newts Logo
unknown
Time Series Management, Scalability, EfficiencyLimited Documentation, Lack of Major Community SupportTime Series, Distributed0
NSDb Logo
  //  
unknown
Distributed Architecture, Real-Time ProcessingEmerging Ecosystem, Integration ChallengesTime Series, Distributed280
OpenTenBase Logo
  //  
unknown
Flexibility, CustomizabilityLack of Enterprise Support, Niche MarketTime Series, In-Memory80
Scalability, High PerformanceLimited Community SupportTime Series, Distributed105390
Efficient XML ProcessingNiche Use CaseNative XML DBMS00
SiriDB Logo
2016
Optimized for Time Series Data, High Write PerformanceLimited Ecosystem IntegrationTime Series, Distributed00
Geospatial Data Handling, Real-Time ProcessingComplex SetupTime Series, Geospatial8990
Handling Vector Data, Scalable ArchitectureEmerging TechnologyVector DBMS, Machine Learning30
High-performance, Low-latency, Efficient storage optimizationComplexity in configuration, Limited community supportKey-Value, Columnar0
High concurrency, Real-time processing, Robust storageProprietary system, Higher costDistributed, In-Memory, SQL00
High availability, Strong consistency, Scalable architectureProprietary technology, Limited community supportRelational, Distributed00
High performance key-value store, ACID transactions, Designed for embedded useLimited community support, Lacks variety in query languagesEmbedded, Key-Value00
Highly optimized for .NET applications, Object-oriented data storageLimited to .NET environments, Niche use casesObject-Oriented, In-Memory, Distributed1300
Integrates with all Azure services, High scalability, Robust analyticsHigh complexity, Cost, Requires Azure ecosystemAnalytical, Distributed, Relational7231744620
High performance, Scalable, ReliableLegacy system, Limited modern integrationHierarchical, Multivalue DBMS1014060
Advanced graph analytics, Proven scalability and reliability, Supports multiple languages like SPARQL and PrologComplex setup and maintenance, Can be expensive for large-scale deploymentsGraph, RDF Stores206120
High-performance for time series data, In-memory processingLimited to time series use cases, Less known in the marketTime Series, In-Memory6940
Scalable, Optimized for time series metricsLimited documentation, Niche use case specificTime Series, Distributed00
Real-time analytics, Faceted search supportComplex integration, Niche marketDistributed, Search Engine0

What is a Database?

A database is an organized collection of data that is stored, managed, and accessed electronically. Databases are essential for storing information in a structured way, making retrieval, updates, and data analysis efficient. Whether it’s your personal contact list or a large-scale enterprise system managing billions of records, databases are foundational to modern computing.

At its core, a database ensures data integrity, scalability, and accessibility. Databases come in many forms, tailored to specific use cases, from relational systems powering financial transactions to cutting-edge vector databases for machine learning models.

Understanding Database Types

Databases are designed with specific functionalities and data models in mind. Here’s a comprehensive list of database types and their primary purposes:

  1. Analytical: Optimized for querying and reporting large datasets, commonly used in business intelligence.
  2. Blockchain: Immutable, decentralized ledgers for secure and transparent transactions.
  3. Columnar: Stores data in columns rather than rows, ideal for analytical workloads.
  4. Content Stores: Designed for managing unstructured data like documents, images, and videos.
  5. Distributed: Spans multiple servers, ensuring reliability and scalability across regions.
  6. Document: Stores semi-structured data like JSON or XML, commonly used in web apps.
  7. Embedded: Lightweight databases embedded into software applications (e.g., mobile apps).
  8. Event Stores: Focused on capturing and storing events, often used in event-driven architectures.
  9. Geospatial: Handles spatial data for maps, geographic applications, and geolocation services.
  10. Graph: Specializes in relationships, storing data as nodes and edges (e.g., social networks).
  11. Hierarchical: Stores data in a tree-like structure, often used in legacy systems.
  12. In-Memory: Stores data in memory for ultra-fast processing.
  13. Key-Value: Simple storage model using key-value pairs, ideal for caching.
  14. Machine Learning: Tailored for storing and retrieving AI/ML model features.
  15. Multivalue DBMS: Allows fields to contain multiple values, simplifying complex data relationships.
  16. Native XML DBMS: Specialized for managing and querying XML data.
  17. NewSQL: Provides scalability of NoSQL with relational data consistency.
  18. Object-Oriented: Stores data as objects, commonly used in object-oriented programming.
  19. RDF Stores: Designed for semantic web and linked data applications.
  20. Relational: The most common type, based on tables and structured query language (SQL).
  21. Search Engine: Optimized for text-based data retrieval and indexing.
  22. Streaming: Processes real-time data streams for low-latency applications.
  23. Time Series: Optimized for time-stamped data (e.g., IoT, financial applications).
  24. Vector DBMS: Stores vector embeddings, ideal for AI/ML-driven search and recommendations.
  25. Wide Column: Schema-less, column-family storage (e.g., Apache Cassandra).

Key Features to Look for in a Database

When evaluating a database, these key features can help you make the right choice:

Choosing the Right Database for Your Project

Selecting a database depends on your specific project requirements. Here's a decision-making guide:

  1. Define Your Use Case: Is it transactional (e.g., e-commerce) or analytical (e.g., reporting)?
  2. Data Type: Choose a database that fits your data structure (e.g., relational for tabular data, graph for relationships).
  3. Scale Needs: Small-scale apps can use lightweight solutions like SQLite, while enterprise-grade systems may need distributed databases like Cassandra.
  4. Budget: Consider open-source options like PostgreSQL or MySQL if cost is a concern.
  5. Flexibility: Choose NoSQL for dynamic schema requirements or frequent changes.
  6. Real-Time Needs: If you need live data, opt for streaming databases like Apache Kafka.

Common Mistakes When Choosing a Database

Avoid these pitfalls to ensure a smooth database implementation:

  1. Ignoring Scalability Needs: Starting with a database that can't grow with your business.
  2. Over-Engineering: Using a complex database for simple applications.
  3. Neglecting Backups: Lack of proper backup strategies leads to data loss.
  4. Underestimating Costs: Forgetting to account for hosting, maintenance, and licensing fees.
  5. Poor Performance Testing: Not benchmarking the database with realistic workloads.

Future Trends in Database Technologies

As technology evolves, databases are becoming more innovative and specialized. Here are some trends shaping the future:

  1. AI and Machine Learning Integration: Databases like Pinecone are optimized for vector embeddings, powering AI-driven applications.
  2. Serverless Databases: Elastic, cost-effective solutions that scale automatically without server management.
  3. Blockchain Databases: Decentralized databases ensuring trust and transparency.
  4. Multi-Model Databases: Combining multiple database types to meet diverse needs.
  5. Graph Databases: Growing in popularity for analyzing relationships in social networks, fraud detection, and more.
  6. Edge Databases: Databases optimized for edge computing, reducing latency in IoT and mobile applications.
  7. Quantum Databases: A future-forward concept leveraging quantum computing for unparalleled data processing.

After exploring the comprehensive database comparison table and diving into the key concepts, types, and trends discussed in this guide, you’re now well-equipped to choose the right database for your specific needs. This combination of data and insights helps you avoid common pitfalls, make informed decisions, and stay ahead of emerging trends. Databases are the backbone of modern technology—mastering them is an invaluable skill in today’s data-driven world.

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