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Valkey: 高性能分布式键值数据库 - 适用于缓存和实时工作负载

A high-performance, flexible, and distributed key-value database optimized for caching, session management, real-time analytics, and other demanding workloads. Valkey provides low-latency data access and scalable architecture.

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Added on 2025年7月2日
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Valkey: 高性能分布式键值数据库 - 适用于缓存和实时工作负载 preview
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Project Introduction

Summary

Valkey is an open-source, in-memory data structure store used as a database, cache, and message broker. It is known for its speed, flexibility, and support for diverse data structures, making it ideal for performance-sensitive applications.

Problem Solved

Modern applications require data stores that can handle massive amounts of concurrent requests with ultra-low latency for tasks like caching, user session management, and real-time data processing. Traditional databases are often too slow or complex for these specific needs. Valkey provides a dedicated solution optimized for these high-throughput, low-latency use cases.

Core Features

Flexible Data Structures

Stores data as key-value pairs, supporting various data structures like strings, hashes, lists, sets, and sorted sets.

High Performance

Designed from the ground up for speed, providing millisecond and sub-millisecond latency for read and write operations.

Distributed Architecture

Supports clustering and replication for horizontal scalability, high availability, and fault tolerance.

Tech Stack

C
Networking
Concurrency
Cluster Management

使用场景

Valkey excels in use cases requiring fast reads and writes, high concurrency, and flexible data structures. Common applications include:

场景一:应用缓存层

Details

Store frequently accessed data in-memory to drastically reduce database load and improve application response times.

User Value

Significantly reduces database latency and increases throughput, improving user experience.

场景二:分布式Session存储

Details

Manage user sessions for web applications, providing fast lookup and modification of session data across distributed servers.

User Value

Enables seamless user experience across load-balanced application instances.

场景三:实时数据处理与分析

Details

Implement real-time leaderboards, counters, rate limiting, and real-time analytics dashboards due to its low-latency operations and data structure support.

User Value

Supports building highly dynamic and responsive features.

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