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The Evolution of In-Memory Data Stores: An Analysis of KeyDB Introduction

KeyDB is not the only NoSQL database on the market, and it's essential to compare it with other popular options. Here's a brief comparison with other NoSQL databases: keydb eng

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 . The Evolution of In-Memory Data Stores: An Analysis

| Metric | Redis 6.2 (single thread) | KeyDB 6.2 (8 threads) | |-----------------------|---------------------------|------------------------| | QPS (SET 50%, GET 50%)| 340k | 1.2M | | P99 latency (ms) | 3.2 | 1.1 | | CPU utilization | 100% (1 core) | 85% (8 cores avg) | KeyDB takes the radical step of making both

For many engineering teams, the decision to use KeyDB comes down to cost and complexity. By getting more performance out of a single large VM, teams can reduce the number of shards required in a cluster. This leads to:

Using memtier_benchmark on AWS c5.4xlarge (16 vCPU):

KeyDB supports Redis Cluster protocol but with some differences in node handoff and failover behavior. In production, recommend using KeyDB Cluster or a proxy like keydb-cluster-proxy . Do not assume 100% parity with Redis Cluster.