: By utilizing all available CPU cores, KeyDB can achieve 5x or more throughput compared to standard Redis.
The KeyDB project began in 2019, born from a fundamental difference in engineering philosophy. The team behind KeyDB believed that the Redis codebase was not fully optimized to take advantage of multiple server cores, forcing users to run clusters of nodes on a single machine to achieve peak throughput.
: Its multi-threaded nature handles complex operations (like SINTER or SUNION on large sets) without "freezing" the database for other users. Quick Comparison Threading Single-threaded (mostly) Multi-threaded Compatibility Industry Standard Drop-in Replacement Replication Primary-Replica Active-Active (Multi-Master) Storage RAM-only (mostly) RAM + NVMe FLASH support
KeyDB introduces a "thread-per-core" design. It uses a small, dedicated set of threads for handling networking I/O and another set for executing commands. This allows KeyDB to handle multiple requests concurrently, dramatically improving throughput and reducing latency [3]. 2. Key-Level Locking keydb eng
To ensure high performance, we do not write one file per key. Instead, we use an append-only log structure similar to RDB/AOF but optimized for random reads.
The KeyDB engine's design directly translates into exceptional performance. A single KeyDB node can achieve over without sharding, matching the throughput of a seven-node Redis cluster.
KeyDB is a high-performance, multithreaded fork of Redis designed to handle high-concurrency workloads by utilizing multiple CPU cores. It maintains full compatibility with the Redis protocol, making it a drop-in replacement for existing Redis setups while offering significantly higher throughput Core Architecture & Key Features Multithreading : By utilizing all available CPU cores, KeyDB
You heavily rely on complex data types (like nested hashes or sorted sets) with high churn rates. Choose the if:
A single KeyDB node can replace a clustered setup of Redis nodes, reducing complexity and infrastructure costs. When to Choose KeyDB Over Redis
: Each connection is assigned to a specific thread upon acceptance. : Its multi-threaded nature handles complex operations (like
While both engines share a common lineage, their underlying execution models differ fundamentally: KeyDB Engine Redis Engine Multithreaded execution Single-threaded execution loop Core Utilization Scales across all available CPU cores Bound to a single CPU core per instance Replication Active-Active (Multi-Master) Active-Passive (Primary-Replica) Storage Tiering Native NVMe Flash storage tiering Primarily RAM-bound Deployment and Configuration
: Unlike Redis's single-threaded event loop, KeyDB uses multiple threads to handle network I/O and query execution.
Go to > BD / UHD > KeyDB to specify the file location. MakeMKV :
: Unlike Redis, KeyDB is fully multithreaded. This allows a single node to handle over 1 million ops/sec , often outperforming Redis by up to 5x on the same hardware.