Here, maxmemory caps the RAM allocated to KeyDB, while cache-memtables reserves memory for caching disk‑resident data during queries. For best performance, use low‑latency NVMe SSDs rather than SATA drives.
You can install it today via Homebrew with brew install keydb or pull the official Docker image to see the speed for yourself.
KeyDB uses separate threads for socket I/O, allowing the main loop to focus on command execution.
Given its architecture and features, KeyDB is well-suited for a variety of engineering use cases: keydb eng
Selecting and tuning the right KeyDB engine allows you to balance ultra-low latency, memory costs, and data persistence. 1. The Core Engines: In-Memory vs. Flash
KeyDB can back up and restore data directly to and from , making disaster recovery and snapshot management much smoother for cloud-native applications. 📊 KeyDB vs. Redis: A Comparison Redis (Standard) Threading Multithreaded Single-threaded (mostly) Scalability Vertical & Horizontal Primarily Horizontal (Cluster) Replication Active-Active (Multi-Master) Master-Replica Complexity Low (Single instance scale) High (Requires clustering for scale) Compatibility 100% Redis Protocol 💡 When to Use KeyDB
KeyDB on FLASH is built on , a high‑performance embedded key‑value store from Facebook. With FLASH enabled, all data is persisted to SSDs, while frequently accessed “hot” data remains in RAM as a cache. When a key is evicted from RAM due to memory pressure, it is not deleted – it is simply moved to FLASH, where it remains accessible. Here, maxmemory caps the RAM allocated to KeyDB,
The primary differentiator of KeyDB is its multi-threaded architecture. While traditional in-memory stores like Redis are primarily single-threaded for command execution, KeyDB utilizes multiple threads to handle network IO and query processing simultaneously. This architectural shift allows KeyDB to fully utilize modern multi-core processors, often achieving significantly higher throughput on a single instance compared to its single-threaded counterparts.
Your data storage needs exceed 100 GBs and scaling RAM is cost-prohibitive.
is an open-source, multithreaded fork of Redis designed for high performance, low latency, and efficient resource utilization . While Redis is traditionally single-threaded, the KeyDB engine utilizes multiple CPU cores to handle network IO and query parsing in parallel. Core Engineering Features KeyDB uses separate threads for socket I/O, allowing
The cornerstone of KeyDB's engineering is its multi-threaded architecture. Unlike traditional Redis which processes commands sequentially in a single event loop, KeyDB distributes work across multiple CPU cores. KeyDB has a MVCC architecture that allows you to execute queries such as KEYS and SCAN without blocking the database and degrading performance.
KeyDB can run without a config file, but it is recommended to use keydb.conf or redis.conf for production.
The core distinction, and the primary "engine" behind its performance, is its multithreaded architecture. The Architecture: Multithreading vs. Single-Threading
threads 8 # Match CPU cores (data threads) server-threads 2 # I/O threads (accept connections) active-replica yes # For Active-Active storage-provider rocksdb # Tiered storage (Flash/SSD) maxmemory-policy allkeys-lru