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光 HikariCP・高性能JDBC连接池
A solid, high-performance, JDBC connection pool designed for minimal latency and maximum throughput. Built for Java and JVM-based applications requiring reliable database connections.
Java
Added on 2025年6月29日20,534
Stars2,984
ForksJava
LanguageProject Introduction
Summary
HikariCP is a lightning-fast, reliable, and simple-to-configure JDBC connection pool. It provides a highly efficient way for Java applications to manage database connections, crucial for high-performance and scalable systems.
Problem Solved
Traditional JDBC connection pools often suffer from performance bottlenecks, complex configurations, and stability issues under high load, leading to slower application response times and increased operational overhead. HikariCP addresses these problems with a focus on speed, simplicity, and robustness.
Core Features
Extreme Performance
Designed from the ground up for speed, achieving market-leading performance in connection acquisition and release.
Simple & Easy to Use
Minimal configuration needed to get started, focusing on sensible defaults while allowing fine-tuning.
Rock-Solid Reliability
Highly stable and reliable, rigorously tested under various load conditions.
Lightweight
Very small JAR size and low memory footprint compared to other pools.
Tech Stack
Java
JDBC
JVM
使用场景
HikariCP is suitable for any Java application requiring robust and fast database access, commonly found in:
高并发Web应用
Details
Improving the responsiveness and scalability of web applications built with frameworks like Spring, Play, or Jakarta EE by efficiently managing database connections for user requests.
User Value
Reduced latency per request, higher throughput, and better resource utilization under heavy load.
分布式微服务架构
Details
Providing fast and reliable database connectivity for individual microservices that need to interact with a database.
User Value
Ensures each service has quick and stable database access, contributing to overall system performance and resilience.
批量处理与数据管道
Details
Accelerating data processing in batch jobs or data pipeline applications that perform numerous database operations.
User Value
Faster execution times for data-intensive tasks, improving overall processing efficiency.
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