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local cache

44 articles · Page 1 of 1
liandk
liandk
Jul 24, 2026 · Fundamentals

Why Every Project Needs Caching – Master Local and Distributed Cache Basics

The article explains the fundamental purpose of caching—placing frequently accessed data in faster storage—to dramatically reduce database load, compares local memory caches with distributed solutions like Redis, outlines their pros, cons, suitable scenarios, and presents a two‑level cache pattern plus common pitfalls such as cache penetration, breakdown, and avalanche.

Rediscachingdistributed cache
0 likes · 6 min read
Why Every Project Needs Caching – Master Local and Distributed Cache Basics
samdeepthink
samdeepthink
Jul 22, 2026 · Backend Development

Why You Should Minimize Local Cache Usage

The article argues that local caches add significant consistency and management complexity, so they should be avoided unless a genuine performance bottleneck exists, illustrating the point with real‑world promotion spikes, GC concerns, and careful off‑heap testing.

GCRedisSystem Design
0 likes · 4 min read
Why You Should Minimize Local Cache Usage
Java Tech Workshop
Java Tech Workshop
Jun 3, 2026 · Backend Development

Why Local Caffeine/Guava Caches Outperform Redis in High‑Concurrency SpringBoot Apps

SpringBoot developers can dramatically boost throughput and cut latency by pairing a microsecond‑level local cache (Caffeine or Guava) with Redis, using a two‑level architecture that isolates hot data in JVM memory, reduces network and serialization overhead, and provides configurable eviction policies for various use cases.

Cache EvictionCaffeineGuava
0 likes · 13 min read
Why Local Caffeine/Guava Caches Outperform Redis in High‑Concurrency SpringBoot Apps
Programmer1970
Programmer1970
May 27, 2026 · Backend Development

Ultimate Cache Consistency Solution for Billion‑Scale Traffic: Canal + MQ + Local Cache

At billion‑level request rates, the traditional cache‑aside pattern fails, so the article proposes a three‑layer architecture—Canal captures MySQL binlog, an MQ (RocketMQ/Kafka) buffers changes, and a coordinated local cache service updates L1 caches with short TTL, achieving high performance and eventual consistency.

Cache ConsistencyCanalDistributed Architecture
0 likes · 12 min read
Ultimate Cache Consistency Solution for Billion‑Scale Traffic: Canal + MQ + Local Cache
Go Development Architecture Practice
Go Development Architecture Practice
Apr 13, 2026 · Backend Development

Why FastCache Is the Go Developer’s Secret Weapon for Ultra‑Fast, Zero‑GC Local Caching

FastCache, an open‑source Go in‑memory cache from the VictoriaMetrics team, delivers extreme speed, zero garbage‑collector pressure, and built‑in thread safety through a shard‑bucket design, while offering a five‑method API that lets developers cache massive key‑value data with minimal configuration, making it ideal for high‑concurrency services and low‑latency workloads.

FastCacheGoThread Safety
0 likes · 7 min read
Why FastCache Is the Go Developer’s Secret Weapon for Ultra‑Fast, Zero‑GC Local Caching
Golang Shines
Golang Shines
Apr 8, 2026 · Backend Development

Deep Dive into FastCache: High‑Performance Local Cache for Go

FastCache is an open‑source Go local‑cache library that delivers extreme speed, zero GC pressure, thread safety, and a five‑method API, making it ideal for high‑concurrency services while providing clear usage guidelines, pitfalls, and suitable scenarios.

FastCacheGohigh concurrency
0 likes · 6 min read
Deep Dive into FastCache: High‑Performance Local Cache for Go
Architect's Journey
Architect's Journey
Nov 29, 2025 · Backend Development

Cache Design Guidelines: Achieve Microsecond Queries and Survive Traffic Spikes

This article outlines practical cache design principles, covering suitable scenarios, health metrics, common pitfalls like avalanche, breakdown and penetration, and concrete implementation rules for both local (Caffeine) and Redis caches to ensure microsecond‑level response and stable high‑traffic performance.

Cache AvalancheCache PenetrationRedis
0 likes · 13 min read
Cache Design Guidelines: Achieve Microsecond Queries and Survive Traffic Spikes
dbaplus Community
dbaplus Community
Aug 11, 2025 · Backend Development

How to Choose and Implement a High‑Performance Local Cache in Java

This article explains why a first‑level local cache is essential for high‑performance services, outlines required cache features, compares four Java implementations (ConcurrentHashMap, Guava, Caffeine, Encache), and provides solutions for consistency, hit‑rate improvement, and technology selection, concluding that Caffeine offers the best performance.

CaffeineEhcacheGuava
0 likes · 11 min read
How to Choose and Implement a High‑Performance Local Cache in Java
Java Captain
Java Captain
Apr 23, 2025 · Backend Development

Design and Selection of Local In‑Memory Caches for High‑Performance Service Architecture

This article explains the role of local in‑memory caches in high‑performance service architectures, compares implementations such as ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache, discusses cache consistency and hit‑rate challenges, and recommends Caffeine as the preferred solution for multi‑level caching with Redis or Memcached.

CaffeineEhcacheGuava
0 likes · 11 min read
Design and Selection of Local In‑Memory Caches for High‑Performance Service Architecture
Selected Java Interview Questions
Selected Java Interview Questions
Apr 16, 2025 · Backend Development

Design and Selection of Local In-Memory Cache Solutions for High-Performance Services

An overview of two‑level caching architecture, the motivations for using local in‑memory caches, essential features of a local cache, comparative analysis of implementations using ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache, and strategies for consistency, hit‑rate improvement, and practical code examples.

CaffeineEhcacheGuava
0 likes · 11 min read
Design and Selection of Local In-Memory Cache Solutions for High-Performance Services
Lobster Programming
Lobster Programming
Jan 20, 2025 · Backend Development

Boost High‑Concurrency Performance: When to Use Redis vs. Local Cache

This article explains why traditional relational databases falter under high‑concurrency loads, introduces caching as a solution, compares Redis distributed caching with local in‑process caching, and shows how combining them into a multi‑level cache can dramatically improve performance and reliability.

Rediscachingdistributed cache
0 likes · 5 min read
Boost High‑Concurrency Performance: When to Use Redis vs. Local Cache
Architect
Architect
Oct 21, 2024 · Backend Development

Choosing the Right Local Cache in Java: From ConcurrentHashMap to Caffeine

This article examines why and how to use local in‑process caches in Java, compares four implementations—ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache—covers essential cache features, consistency challenges, hit‑rate optimization, and recommends Caffeine as the most performant choice for a two‑level caching architecture.

Cache ConsistencyCaffeineConcurrentHashMap
0 likes · 11 min read
Choosing the Right Local Cache in Java: From ConcurrentHashMap to Caffeine
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 26, 2023 · Backend Development

How a New Cache Design Boosted Logistics Pricing QPS Five‑Fold

This article reviews the performance challenges of the logistics pricing engine, explains the limitations of the previous 1.0 optimizations, and details the design and implementation of a new 2.0 cache strategy using Tair and local caches, key‑value modeling, pre‑heating, updates, and bottleneck mitigation, achieving the required QPS.

Tairbackendcaching
0 likes · 19 min read
How a New Cache Design Boosted Logistics Pricing QPS Five‑Fold
Sanyou's Java Diary
Sanyou's Java Diary
May 8, 2023 · Backend Development

Choosing the Right Cache: Local vs Distributed Strategies Explained

This article explores how caching accelerates high‑concurrency systems by reducing CPU and I/O load, compares local and distributed cache types, reviews Java cache implementations and frameworks, and presents real‑world multi‑level cache designs and pitfalls to help you select the optimal solution.

cachingdistributed cachelocal cache
0 likes · 12 min read
Choosing the Right Cache: Local vs Distributed Strategies Explained
政采云技术
政采云技术
Apr 25, 2023 · Backend Development

Cache System Overview, Architecture Evolution, Pain Points, and Best Practices

This article explains the fundamentals of cache systems, describes the evolution from no‑cache to distributed and local caches, analyzes common challenges such as consistency, hot‑key detection, and cache avalanche, and provides practical guidelines and real‑world lessons for designing effective backend caching solutions.

Backend Performancearchitecturecaching
0 likes · 14 min read
Cache System Overview, Architecture Evolution, Pain Points, and Best Practices
Architecture Digest
Architecture Digest
Mar 14, 2023 · Backend Development

Design and Selection of Local In-Memory Cache Solutions for Two-Level Cache Architecture

An overview of two-level cache architecture explains why local in-memory caches are needed, outlines essential cache features, compares implementations using ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache with code examples, and discusses consistency, hit-rate improvement, and technology selection, recommending Caffeine for best performance.

CaffeineEhcacheGuava
0 likes · 11 min read
Design and Selection of Local In-Memory Cache Solutions for Two-Level Cache Architecture
Top Architect
Top Architect
Dec 14, 2022 · Backend Development

Cache Basics: Concepts, Types, Advantages, and Implementation Strategies

This article explains the fundamentals of caching, why caches (especially Redis) are essential for high‑performance and high‑concurrency scenarios, describes local, distributed, and multi‑level cache architectures, outlines their pros and cons, and provides practical implementation guidance.

Multi-Level CacheRedisdistributed cache
0 likes · 10 min read
Cache Basics: Concepts, Types, Advantages, and Implementation Strategies
Selected Java Interview Questions
Selected Java Interview Questions
Dec 2, 2022 · Backend Development

Understanding Cache: Concepts, Types, and Implementation in Backend Development

This article explains the fundamentals of caching, why caches like Redis are essential for high‑performance and high‑concurrency backend systems, and compares local, distributed, and multi‑level cache architectures, including their advantages, drawbacks, and typical implementation approaches.

Multi-Level Cachebackendlocal cache
0 likes · 9 min read
Understanding Cache: Concepts, Types, and Implementation in Backend Development
Past Memory Big Data
Past Memory Big Data
Nov 15, 2022 · Big Data

How Uber Accelerated Presto Queries with Alluxio Local Cache

Uber processes over 500,000 daily Presto queries across 20 clusters handling more than 50 PB of data, and by deploying Alluxio Local Cache on NVMe disks they raised cache‑hit rates from roughly 65% to over 90% while addressing real‑time partition updates, node churn, and cache‑size constraints.

AlluxioBig DataMetadata
0 likes · 15 min read
How Uber Accelerated Presto Queries with Alluxio Local Cache
Java Architect Essentials
Java Architect Essentials
Sep 27, 2022 · Backend Development

How to Combine Redis and Guava for Lazy‑Loading Cache in Java

This article explains how to reduce Redis read/write pressure by introducing a Guava local cache for lazy loading, presents design diagrams, provides complete Java code examples for both simple lazy caching and a microservice‑oriented device‑increment cache, and discusses the advantages, disadvantages, and practical considerations of each approach.

GuavaMicroservicesRedis
0 likes · 11 min read
How to Combine Redis and Guava for Lazy‑Loading Cache in Java
Tencent Cloud Developer
Tencent Cloud Developer
Apr 21, 2022 · Backend Development

Local Cache Solutions in Golang: A Comprehensive Guide to Open-Source Components

The guide reviews the essential requirements for Go local caching and compares seven open‑source caches—freecache, bigcache, fastcache, offheap, groupcache, ristretto, and go‑cache—while detailing the sharded, lock‑reduced designs of freecache, bigcache, fastcache, and offheap, and explains how off‑heap allocation or pointer‑free maps achieve near zero‑GC performance.

FastCacheFreeCacheOff-heap memory
0 likes · 10 min read
Local Cache Solutions in Golang: A Comprehensive Guide to Open-Source Components
Yanxuan Tech Team
Yanxuan Tech Team
Apr 7, 2022 · Backend Development

Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies

This article explains why caching is essential for reducing CPU and I/O pressure, outlines key cache attributes such as throughput and hit rate, compares popular local cache libraries, describes distributed cache options, and details the design, consistency, monitoring, and hot‑key handling of a transparent multilevel cache architecture.

Heliosconsistencydistributed cache
0 likes · 20 min read
Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Apr 6, 2022 · Backend Development

Server-Side Caching: Local, Distributed, and Multi-Level Cache Architecture Practices

Server‑side caching improves performance by trading space for time, using local caches like HashMap, Guava, Ehcache, and Caffeine, distributed caches such as Redis, and multi‑level architectures that combine in‑process, distributed, and database layers, while employing consistency patterns, monitoring, and hot‑key detection.

Cache ConsistencyCaffeineHot Key Detection
0 likes · 16 min read
Server-Side Caching: Local, Distributed, and Multi-Level Cache Architecture Practices
IT Architects Alliance
IT Architects Alliance
Jul 24, 2021 · Backend Development

Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation

The article introduces Youzan's Transparent Multilevel Cache (TMC), detailing its three‑layer architecture, hotspot detection and local caching mechanisms, integration approaches for Java applications, stability and consistency features, and performance results from real‑world e‑commerce campaigns.

cachedistributed systemshotspot detection
0 likes · 13 min read
Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation
Selected Java Interview Questions
Selected Java Interview Questions
Jul 13, 2021 · Backend Development

Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache for High‑Performance Applications

The article introduces Transparent Multilevel Cache (TMC), a Youzan PaaS solution that adds application‑level hotspot detection, local caching, and hit‑rate statistics to distributed caches, explains its architecture, workflow, consistency guarantees, and shows performance improvements during high‑traffic events.

hotspot detectionjavalocal cache
0 likes · 14 min read
Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache for High‑Performance Applications
New Oriental Technology
New Oriental Technology
Jun 17, 2021 · Backend Development

Cache Basics, Types, Patterns, and Common Issues

This article explains why caching is used, distinguishes between local and distributed caches, compares popular Java cache libraries, describes Redis and Memcached differences, outlines the Cache‑Aside pattern, and discusses common cache problems such as inconsistency, penetration, breakdown, avalanche, hot‑key detection, and their mitigation strategies.

Redisdistributed cachejava
0 likes · 15 min read
Cache Basics, Types, Patterns, and Common Issues
Top Architect
Top Architect
Jun 7, 2021 · Backend Development

Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation

The article presents the design and implementation of Transparent Multilevel Cache (TMC), a three‑layer caching solution that adds hotspot detection and local cache to reduce distributed cache pressure, explains its transparent Java integration, describes the sliding‑window hotspot discovery pipeline, and showcases performance gains in real‑world e‑commerce campaigns.

distributed systemshotspot detectionjava
0 likes · 14 min read
Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation
IT Architects Alliance
IT Architects Alliance
May 30, 2021 · Backend Development

Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation

The article introduces Transparent Multilevel Cache (TMC), a comprehensive caching solution that adds hotspot detection and local caching to existing distributed cache systems, explains its three‑layer architecture, transparent Java integration, real‑time hotspot discovery process, and demonstrates performance gains in high‑traffic e‑commerce scenarios.

Rediscachedistributed systems
0 likes · 13 min read
Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache Implementation
21CTO
21CTO
May 30, 2021 · Backend Development

How Transparent Multilevel Cache (TMC) Eliminates Hotspot Bottlenecks in Java Services

The article introduces Youzan's Transparent Multilevel Cache (TMC), explains why hotspot cache access harms e‑commerce applications, describes its three‑layer architecture, details the Java client integration with Hermes‑SDK for automatic hotspot detection and local caching, and presents real‑world performance gains during large‑scale promotional events.

cachedistributed systemshotspot detection
0 likes · 14 min read
How Transparent Multilevel Cache (TMC) Eliminates Hotspot Bottlenecks in Java Services
Java Backend Technology
Java Backend Technology
May 20, 2021 · Backend Development

How Transparent Multilevel Cache (TMC) Supercharges Java Application Performance

The article explains Youzan's Transparent Multilevel Cache (TMC), a solution that automatically detects cache hotspots, adds an application‑level local cache, and provides hit statistics to reduce load on distributed caches, improve consistency, and boost performance for high‑traffic e‑commerce scenarios.

cachedistributed systemshotspot detection
0 likes · 15 min read
How Transparent Multilevel Cache (TMC) Supercharges Java Application Performance
DeWu Technology
DeWu Technology
May 14, 2021 · Backend Development

Local and Distributed Caching: Concepts and Implementations

In high‑traffic e‑commerce systems, caching—ranging from simple in‑JVM HashMap caches to Guava, Caffeine, and Redis distributed stores—reduces latency by applying eviction policies such as FIFO, LRU, LFU, or W‑TinyLFU, while employing consistency strategies like expiration, write‑through, and cache‑aside to mitigate breakdown, avalanche, and penetration issues.

CaffeineGuavaRedis
0 likes · 20 min read
Local and Distributed Caching: Concepts and Implementations
vivo Internet Technology
vivo Internet Technology
Apr 21, 2021 · Backend Development

Understanding and Configuring Caffeine Cache in Java Applications

Understanding Caffeine Cache in Java involves using its builder for options like expiration, refresh, and weight‑based eviction, recognizing that configuring both expireAfterWrite and expireAfterAccess is redundant, grasping core methods such as isBounded, refreshes, computeIfAbsent, and avoiding common pitfalls like mis‑ordered expiration settings, blocking loaders, cache penetration, and mutable cached objects.

Cache ConfigurationCache EvictionCaffeine cache
0 likes · 15 min read
Understanding and Configuring Caffeine Cache in Java Applications
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Dec 1, 2020 · Backend Development

Mastering Cache: Core Concepts, Pitfalls, and Patterns for Scalable Systems

Cache leverages the space‑time trade‑off to boost performance, but introduces complexity; this guide explains its fundamental idea, local vs distributed solutions, popular Java caching libraries, and key read/write patterns such as Cache‑Aside, Read‑Through, and Write‑Behind, highlighting benefits, drawbacks, and best‑practice considerations.

System Designcache patternscaching
0 likes · 13 min read
Mastering Cache: Core Concepts, Pitfalls, and Patterns for Scalable Systems
Architecture Digest
Architecture Digest
Nov 8, 2020 · Backend Development

Key Considerations and Implementation Strategies for a Local Cache in Java

This article outlines the essential design considerations for building a local cache—such as data structures, size limits, eviction policies, expiration, thread safety, simple APIs, persistence, and blocking mechanisms—and demonstrates concrete Java implementations with code examples.

MyBatisThread Safetyeviction policy
0 likes · 11 min read
Key Considerations and Implementation Strategies for a Local Cache in Java
Top Architect
Top Architect
Aug 2, 2020 · Backend Development

Key Considerations for Implementing a Local Cache in Java

This article outlines the essential design considerations for building a local cache in Java, covering data structures, capacity limits, eviction policies, expiration handling, thread safety, blocking mechanisms, simple APIs, and optional persistence, with illustrative code examples.

concurrencyevictionjava
0 likes · 13 min read
Key Considerations for Implementing a Local Cache in Java
Top Architect
Top Architect
May 6, 2020 · Backend Development

Key Considerations and Implementation Strategies for a Local Cache

This article outlines the essential considerations for designing a local cache—including data structures, size limits, eviction policies, expiration, thread safety, blocking mechanisms, simple APIs, and persistence—and demonstrates implementation approaches with Java code examples such as Map usage, synchronized caches, and memoization techniques.

evictionjavalocal cache
0 likes · 11 min read
Key Considerations and Implementation Strategies for a Local Cache
Java Captain
Java Captain
Dec 14, 2019 · Backend Development

Key Considerations and Implementation Strategies for a Local Cache in Java

This article outlines the essential design points for a local Java cache—including data structures, size limits, eviction policies, expiration handling, thread safety, blocking mechanisms, simple APIs, and persistence options—while providing concrete code examples and implementation guidance.

Persistencecacheconcurrency
0 likes · 12 min read
Key Considerations and Implementation Strategies for a Local Cache in Java
Amap Tech
Amap Tech
Aug 13, 2019 · Backend Development

Cache Strategies and Framework Selection for High‑Performance Systems

To achieve low‑latency, high‑throughput data access in systems like Gaode’s navigation service, the article advises evaluating CPU and I/O bottlenecks, choosing between local (HashMap/ConcurrentHashMap or Caffeine) and distributed caches (Redis preferred), applying appropriate eviction, TTL, and consistency patterns, and mitigating cache penetration, breakdown, and avalanche risks.

Cache strategiesRediscaching
0 likes · 26 min read
Cache Strategies and Framework Selection for High‑Performance Systems
Youzan Coder
Youzan Coder
Nov 23, 2018 · Cloud Computing

Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache in Youzan PaaS

Youzan’s Transparent Multilevel Cache (TMC) adds automatic hotspot detection and a 64 MB local cache to existing distributed caches via a Hermes‑SDK‑augmented Jedis client, delivering transparent Java integration, strong consistency, up to 80 % local‑hit rates, and improved QPS during high‑traffic events.

PaaScachedistributed systems
0 likes · 15 min read
Transparent Multilevel Cache (TMC): Architecture, Hotspot Detection, and Local Cache in Youzan PaaS
Architects' Tech Alliance
Architects' Tech Alliance
Aug 29, 2018 · Backend Development

Comprehensive Guide to Effective Caching Strategies and Best Practices

This article explains when caching is needed, how to choose appropriate in‑process and distributed caches, design multi‑level cache architectures, handle cache updates, avoid common pitfalls such as penetration, breakdown and avalanche, and provides practical advice on serialization, GC tuning, monitoring, and framework selection.

Cache strategiesdistributed cachelocal cache
0 likes · 19 min read
Comprehensive Guide to Effective Caching Strategies and Best Practices