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dragonflydb/dragonfly

📈 Trending★ 30,501C++Audience · ops devopsComplexity · 2/5ActiveLicenseSetup · moderate

TLDR

A drop-in replacement for Redis that uses all CPU cores simultaneously, delivering up to 25x higher throughput and 30% better memory efficiency.

Mindmap

mindmap
  root((Dragonfly))
    What it does
      In-memory data store
      Drop-in Redis replacement
      Multi-core processing
    Performance gains
      25x throughput boost
      30% memory savings
      Lower memory spikes
    Tech approach
      Fiber-based concurrency
      C++ implementation
      Redis API compatible
    Use cases
      Cache layer scaling
      High-throughput systems
      Cost optimization
    Compatibility
      Redis commands
      Memcached commands
      No code changes needed

Things people build with this

USE CASE 1

Replace Redis in production systems to handle higher request throughput without adding more servers.

USE CASE 2

Reduce infrastructure costs by running the same workload on fewer, cheaper server instances.

USE CASE 3

Cache frequently-accessed data with better memory efficiency than Redis on multi-core machines.

Tech stack

C++Redis protocolMemcached protocolFibers

Getting it running

Difficulty · moderate Time to first run · 30min

Requires building from C++ source code; pre-built binaries may not be available for all platforms.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and license text.

In plain English

Dragonfly is an in-memory data store, a database that keeps all its data in RAM rather than on disk, which makes reads and writes extremely fast. It is designed as a drop-in replacement for Redis and Memcached, two widely-used in-memory stores. Because Dragonfly implements the same commands and connection protocol as Redis and Memcached, existing applications can switch to it without changing any of their code. The core problem Dragonfly addresses is that Redis is fundamentally single-threaded: it can only use one CPU core at a time. On modern servers with many cores, this becomes a ceiling on performance. Dragonfly is built from the ground up to use all available CPU cores simultaneously using a technique called fibers (lightweight threads managed within the program rather than by the operating system). According to the README's benchmarks, this allows Dragonfly to deliver up to 25 times more request throughput than Redis on high-core-count machines, while also using significantly less memory, the README reports 30% better memory efficiency in idle state and far less memory spike during data snapshots. An operations team or backend developer would switch to Dragonfly when Redis is becoming the performance bottleneck in their system, when they want the same caching behavior but on smaller, cheaper server instances, or when they need to handle higher throughput without horizontally scaling to a Redis cluster. It is written in C++ and is fully compatible with Redis API commands and Memcached commands.

Copy-paste prompts

Prompt 1
How do I migrate my Redis instance to Dragonfly without changing my application code?
Prompt 2
What are the performance benchmarks comparing Dragonfly to Redis on a 32-core server?
Prompt 3
Show me how to set up Dragonfly as a drop-in replacement for my existing Redis cache layer.
Prompt 4
How does Dragonfly's fiber-based concurrency model allow it to use multiple CPU cores?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.