Dragonfly Has a Free API: The Redis-Compatible Cache That's 25x Faster

#redis #database #performance #caching

Redis is single-threaded. In 2026, your server has 64 cores. Dragonfly uses all of them.

What Is Dragonfly?

Dragonfly is a Redis/Memcached-compatible in-memory datastore that's multi-threaded by design. Same API, same commands, 25x more throughput on modern hardware.

# Drop-in Redis replacement
docker run --ulimit memlock=-1 -p 6379:6379 docker.dragonflydb.io/dragonflydb/dragonfly

# Use your existing Redis client — no changes needed
redis-cli -p 6379
> SET hello world
> GET hello
"world"

Why Dragonfly Over Redis

1. Multi-threaded — Redis uses 1 core. Dragonfly uses all cores. On a 64-core machine, that's 25x more throughput.

2. Memory efficient — Dragonfly uses up to 40% less memory for the same dataset. Its novel data structure (dash table) is more compact than Redis's hash tables.

3. Snapshots without forks — Redis forks the process for RDB snapshots, temporarily doubling memory usage. Dragonfly snapshots without forking.

Metric	Redis	Dragonfly
Throughput (64 cores)	400K ops/s	4M ops/s
Memory for 10M keys	1.5GB	900MB
Snapshot memory spike	2x	None
Max connections	~10K	1M+

Compatibility

# Python — same redis-py library
import redis
r = redis.Redis(host='localhost', port=6379)
r.set('key', 'value')
r.get('key')  # b'value'
r.lpush('list', 'a', 'b', 'c')
r.hset('hash', mapping={'field1': 'val1', 'field2': 'val2'})