For keydb eng teams ready to test: Do not run synthetic benchmarks only. Mirror your production traffic using redis-benchmark or memtier. You will likely see throughput double without changing a single line of application code.
KeyDB proves that the original Redis architecture was a masterpiece of single-threaded simplicity—but the future of in-memory data stores is parallel.
Start your migration today:
# On Ubuntu:
curl -fsSL https://packages.keydb.dev/keydb.gpg | sudo gpg --dearmor -o /usr/share/keyrings/keydb.gpg
sudo apt update && sudo apt install keydb
sudo systemctl start keydb
Test it. Benchmark it. Break it. That is the engineering way.
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| Feature | KeyDB | Redis OSS | |---------|-------|------------| | Multithreaded | ✅ Native | ❌ (Enterprise only) | | Flash storage tier | ✅ RocksDB | ❌ (Redis Enterprise) | | Active-Active geo | ✅ Built-in | ❌ (Enterprise) | | Module compatibility | ✅ Full | ✅ | | Community size | Medium | Very Large |
Published benchmarks (KeyDB team, Snap Inc.) on a 40-core machine with memtier_benchmark: For keydb eng teams ready to test: Do
| Operation | Redis 6.0 (single-thread) | KeyDB (16 threads) | Improvement | |-----------|----------------------------|--------------------|--------------| | SET (QPS) | 450k | 4.2M | 9.3x | | GET (QPS) | 520k | 6.1M | 11.7x | | 50/50 R/W | 480k | 5.8M | 12x | | 99th %ile latency | 1.2ms | 0.6ms | 2x |
Crucially, scaling is near-linear up to ~24 cores, then allocator contention and cache coherence traffic cause diminishing returns. Test it
The most common misconception is that KeyDB simply adds threading to Redis. Redis 6.0 introduced threaded I/O (reading/writing network sockets in parallel), but the core command execution remained single-threaded. KeyDB takes the radical step of making both I/O and command execution parallel.