A Modern Redis Replacement

Probably the fastest memory store in the universe.
Fully compatible with Redis™* and Memcached.
Scales easily to handle millions of QPS and hundreds of GBs of memory.

Get Dragonfly

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  # Dragonfly self managed is free and takes 10 seconds to setup.
  # Get Dragonfly running
  docker run --network=host --ulimit memlock=-1 docker.dragonflydb.io/dragonflydb/dragonfly

  # Test with redis-cli
  redis-cli PING
  
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Millions of operations per second from a single instance

Simple

Engineered to hide all complexities behind the scenes allowing you to avoid working with complex cluster configurations

Cost Effective

Dragonfly is optimized to utilize all hardware resources to delivery the same workloads at a fraction of the costs

Robust

Dragonfly utilizes state of the art academic algorithms to provide strict serializability guarantees in a multi-threaded architecture

Memory Efficient

Dragonfly internal data structures are memory optimized to consume 20%-40% less memory resources

Dragonfly VS Redis

Dragonfly is compatible with Redis APIs, implemented by a modern engine architecture. Check out the comparison below. Click the links for more details.
DragonflyRedis
Redis API compatible
Snapshot persistency
Lua5.4.45.1
QPS per instance3M200K
Async core
LRFU eviction
Memcached API compatible
Native Open Telemetry

Simple to scale

Dragonfly takes advantage of every core, memory and network byte to scale vertically with your instance resources. It grows with you from the first bytes to hundreds of gigabytes of in-memory datastore on the single instance.

Do more for less

Designed from the ground up in C++ to extract the most value from your infrastructure. Dragonfly takes advantage of every core, memory and network byte to scale vertically with your instance resources.

Built for performance

Dragonfly is a new in-memory engine, optimized for throughput, using a thread-per-core architecture without locks to deliver stable and low latencies. Using true async interfaces, Dragonfly takes advantage of all hardware resources to their limit.