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valkey-io/valkey

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TLDR

Open-source in-memory database for ultra-fast caching and real-time features. Community fork of Redis with the same API, optimized for sub-millisecond data access.

Mindmap

mindmap
  root((Valkey))
    What it does
      In-memory data store
      Key-value pairs
      Rich data structures
    Performance
      Sub-millisecond access
      Caching layer
      Real-time workloads
    Features
      Clustering support
      Replication
      Plugin system
    Use cases
      Session management
      Rate limiting
      Leaderboards
      Message queues
    Tech details
      Written in C
      Linux, macOS, BSD
      Network server

Things people build with this

USE CASE 1

Cache expensive database queries so your app responds instantly without hitting the database every time.

USE CASE 2

Store user session data and authentication tokens for fast login and session validation.

USE CASE 3

Build real-time leaderboards, counters, and rate limiters that update across multiple users instantly.

USE CASE 4

Queue and process messages between services with sub-millisecond latency.

Tech stack

CLinuxmacOSBSD

Getting it running

Difficulty · moderate Time to first run · 30min

Requires compiling from C source; Linux/macOS/BSD only, no Windows native support.

Use freely for any purpose, including commercial use. Fully open-source with no restrictive licensing.

In plain English

Valkey is a high-performance in-memory data store, a database that keeps data in RAM rather than on disk so that reads and writes are extremely fast. It was forked (copied and independently continued) from the open-source Redis project just before Redis changed to a more restrictive license, making Valkey the community-maintained, fully open-source successor. It is optimized for caching (temporarily storing the results of expensive computations so they can be reused instantly) and real-time workloads like session management, rate limiting, leaderboards, and message queuing. Valkey works by storing data as key-value pairs, think of it like a giant dictionary where you look up a value by name. Beyond simple strings, it supports rich data structures such as lists, sets, sorted sets, and hashes. It runs as a standalone server process that your application connects to over a network, and it supports clustering (distributing data across multiple servers) and replication (keeping copies for reliability). A plugin system allows developers to add custom data structures. You would use Valkey when your application needs sub-millisecond data access, for example, caching database query results, storing user session data, or powering a real-time feature like live notifications. It is written in C and runs on Linux, macOS, and BSD systems.

Copy-paste prompts

Prompt 1
Show me how to set up Valkey as a caching layer for my application and connect to it from my code.
Prompt 2
How do I use Valkey's sorted sets to build a real-time leaderboard that updates instantly?
Prompt 3
Walk me through setting up Valkey clustering and replication for high availability.
Prompt 4
How do I store and retrieve user session data in Valkey with expiration times?
Prompt 5
Show me how to use Valkey's pub/sub feature to send real-time notifications between services.
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