KeyDB is designed to be a . If your application already uses a Redis client (like redis-py , ioredis , or go-redis ), you can point it at a KeyDB server without changing a single line of code.
To handle datasets larger than available RAM, KeyDB offers a . It uses NVMe SSDs to extend memory capacity, significantly reducing the cost-per-gigabyte while maintaining high performance. 3. Direct S3 Backup keydb eng
: By utilizing all available CPU cores, KeyDB can achieve 5x or more throughput compared to standard Redis. KeyDB is designed to be a
: When you want to avoid the operational overhead of managing a Redis Cluster but need "Cluster-level" performance. 🔧 Getting Started It uses NVMe SSDs to extend memory capacity,
The core differentiator for KeyDB is its . While Redis historically handles commands on a single event loop, KeyDB distributes network IO and query execution across multiple threads.