BestHub
Sign in
Tagged articles

sharding

677 articles · Page 5 of 7
Tencent Cloud Developer
Tencent Cloud Developer
Dec 10, 2021 · Databases

MongoDB Architecture and Performance Optimizations for Tencent Cloud K‑Song Feed Service

The article details how Tencent Cloud’s K‑Song feed service, serving over 150 million daily users, was engineered with a read‑expansion model, cached results, auxiliary index tables, hashed sharding, write‑concern tuning, disabled chain replication, and WiredTiger and backup optimizations, achieving sub‑10 ms write latency and significantly lower CPU and slow‑query rates.

MongoDBTencent Cloudcache
0 likes · 17 min read
MongoDB Architecture and Performance Optimizations for Tencent Cloud K‑Song Feed Service
IT Architects Alliance
IT Architects Alliance
Dec 9, 2021 · Backend Development

How to Build a Billion‑User Scalable User Center: Architecture, APIs, Token Fallback, and Security

This article presents a comprehensive, practical design for an ultra‑large‑scale user center, covering microservice architecture, API separation, token generation with graceful degradation, data‑sharding strategies, password encryption, asynchronous processing, and detailed monitoring to ensure high availability, performance, and security.

SecurityTokenmicroservices
0 likes · 16 min read
How to Build a Billion‑User Scalable User Center: Architecture, APIs, Token Fallback, and Security
Java Interview Crash Guide
Java Interview Crash Guide
Dec 7, 2021 · Databases

Why Traditional Pagination Fails After Sharding and How to Solve It

When a table grows beyond ten million rows, sharding it across multiple databases improves performance, but the usual LIMIT offset, pagesize pagination breaks, leading to missing or incorrect records; this article examines why simple merge approaches fail and evaluates global, secondary query, and no‑skip paging strategies, highlighting their trade‑offs.

MySQLSQLdatabase
0 likes · 12 min read
Why Traditional Pagination Fails After Sharding and How to Solve It
dbaplus Community
dbaplus Community
Dec 6, 2021 · Backend Development

Mastering Elasticsearch Index Design: From Sharding to Mapping

This comprehensive guide explains Elasticsearch index design, covering shard and replica planning, settings optimization, dynamic and static mappings, template management, lifecycle automation, and practical best‑practice recommendations for high‑performance, stable search clusters.

Mappingindex designlifecycle management
0 likes · 26 min read
Mastering Elasticsearch Index Design: From Sharding to Mapping
Programmer DD
Programmer DD
Nov 28, 2021 · Backend Development

Master MyBatis with Mybatis-Mate: Sharding, Encryption, Auditing and More

This article introduces Mybatis-Mate, an enterprise‑level MyBatis extension that provides sharding, data audit, sensitive‑word filtering, field encryption, dictionary binding, data permission, dynamic DDL generation and other features, and shows how to integrate and use them with practical code examples.

Data AuditingJavaMyBatis
0 likes · 14 min read
Master MyBatis with Mybatis-Mate: Sharding, Encryption, Auditing and More
Aikesheng Open Source Community
Aikesheng Open Source Community
Nov 22, 2021 · Databases

DBLE 3.21.10.0 Release Notes: New Features, Bug Fixes, and LTS Updates

The article provides a detailed overview of DBLE version 3.21.10.0, covering project background, three major new features—including single‑node detach/reattach, enhanced traffic control, and default sharding mode—along with a full list of release notes, bug fixes, incompatibilities, and subsequent LTS patch updates.

DBLEDatabase Proxydistributed middleware
0 likes · 8 min read
DBLE 3.21.10.0 Release Notes: New Features, Bug Fixes, and LTS Updates
政采云技术
政采云技术
Nov 18, 2021 · Databases

Elasticsearch Series Part 1: Introduction to System Concepts and Read/Write Flow

This article introduces Elasticsearch as a distributed, high‑performance search engine, explains its cluster architecture, node roles, shard and replica mechanisms, write and refresh processes, and outlines search handling techniques such as pagination, scroll and search‑after with practical curl examples.

Distributed SearchElasticsearchSearch API
0 likes · 11 min read
Elasticsearch Series Part 1: Introduction to System Concepts and Read/Write Flow
Top Architect
Top Architect
Nov 13, 2021 · Backend Development

Introducing MyBatis-Mate: Enterprise‑Level Features for MyBatis‑Plus

This article introduces MyBatis‑Mate, an official MyBatis‑Plus extension that provides enterprise‑grade capabilities such as sharding, data auditing, field encryption, dictionary binding, sensitive data masking, automatic DDL maintenance, dynamic data‑source switching, performance logging, and fine‑grained data‑scope control, all illustrated with practical code examples.

JavaMyBatisORM
0 likes · 15 min read
Introducing MyBatis-Mate: Enterprise‑Level Features for MyBatis‑Plus
Java Architect Essentials
Java Architect Essentials
Nov 8, 2021 · Operations

Scaling RabbitMQ to Million‑Message Throughput: Architecture, Sharding, Federation, and High Availability

This article explains how to horizontally scale RabbitMQ clusters to achieve million‑message per second throughput, covering Google’s large‑scale test setup, sharding and consistent‑hash plugins, federation, high‑availability mirroring, reliability mechanisms, and practical deployment tips for production environments.

RabbitMQhigh availabilitysharding
0 likes · 23 min read
Scaling RabbitMQ to Million‑Message Throughput: Architecture, Sharding, Federation, and High Availability
dbaplus Community
dbaplus Community
Nov 7, 2021 · Databases

Why Distributed Databases Matter: From Early DBMS to Modern NewSQL

This article traces the evolution of database systems—from the first network and hierarchical models through relational databases, NoSQL sharding, and finally modern distributed SQL—explaining why distributed databases emerged, how they handle data distribution, consistency, SQL-to‑KV mapping, and transaction challenges.

NewSQLSQL to KVconsensus algorithms
0 likes · 16 min read
Why Distributed Databases Matter: From Early DBMS to Modern NewSQL
Top Architect
Top Architect
Nov 6, 2021 · Databases

Understanding Database Sharding: Partitioning Strategies and When to Use Them

This article explains the concepts, characteristics, and practical scenarios of database sharding—including vertical and horizontal table partitioning as well as vertical and horizontal database partitioning—helping developers decide when and how to apply each strategy to improve scalability and performance.

Horizontal PartitioningMySQLVertical Partitioning
0 likes · 10 min read
Understanding Database Sharding: Partitioning Strategies and When to Use Them
Java Captain
Java Captain
Nov 6, 2021 · Databases

Introducing mybatis-mate: Enterprise‑Level MyBatis Extension for Sharding, Data Encryption, Auditing, and More

The article presents mybatis-mate, an enterprise‑grade MyBatis module that provides sharding, data auditing, sensitive‑word filtering, field encryption, dictionary write‑back, data permission, automatic DDL maintenance, dynamic multi‑datasource switching, and distributed transaction logging, offering developers a more agile and elegant way to handle data.

Data AuditingORMdata encryption
0 likes · 15 min read
Introducing mybatis-mate: Enterprise‑Level MyBatis Extension for Sharding, Data Encryption, Auditing, and More
ITPUB
ITPUB
Nov 5, 2021 · Databases

Why Distributed Databases Face Consistency Challenges and How to Address Them

The article explains how distributed database systems appear as a single logical database but operate over a network of nodes, detailing failures, stale reads, consistency models, architecture anomalies, sharding, replication, and various read/write scenarios that illustrate the complexity of achieving strong consistency.

CAP theoremconsistencydistributed databases
0 likes · 16 min read
Why Distributed Databases Face Consistency Challenges and How to Address Them
Top Architect
Top Architect
Oct 28, 2021 · Databases

ShardingSphere-JDBC MySQL Master‑Slave Replication, Redo Log, Binlog and Sharding Implementation Guide

This article provides a step‑by‑step tutorial on configuring MySQL master‑slave replication with Docker, explains redo log and binlog mechanisms, demonstrates two‑phase commit, and shows how to use ShardingSphere‑Jdbc for read/write splitting and sharding with detailed Spring Boot examples and code snippets.

JavaMySQLReplication
0 likes · 21 min read
ShardingSphere-JDBC MySQL Master‑Slave Replication, Redo Log, Binlog and Sharding Implementation Guide
High Availability Architecture
High Availability Architecture
Oct 26, 2021 · Databases

Practical Guide to Horizontal Database Sharding: Design Principles, Common Schemes, and Expansion Strategies

This article explains the background, design criteria, and practical implementations of horizontal database sharding—including range, hash, gene, routing‑table, and consistent‑hash methods—while discussing common pitfalls, data‑skew mitigation, and both doubling and consistent‑hash expansion techniques for MySQL clusters.

Database ScalingHorizontal PartitioningMySQL
0 likes · 24 min read
Practical Guide to Horizontal Database Sharding: Design Principles, Common Schemes, and Expansion Strategies
dbaplus Community
dbaplus Community
Oct 21, 2021 · Databases

How We Scaled an E‑commerce Order System with Sharding, Consistent Hashing, and Zero‑Downtime Migration

This article details how a rapidly growing e‑commerce platform migrated from a single MySQL instance to a 16‑shard architecture using Sharding‑Jdbc, introduced consistent‑hashing to mitigate data skew, leveraged ES+HBase for multi‑dimensional queries, and implemented zero‑downtime migration strategies such as dual‑write and Canal replication.

Database ScalingElasticsearchHBase
0 likes · 21 min read
How We Scaled an E‑commerce Order System with Sharding, Consistent Hashing, and Zero‑Downtime Migration
ITPUB
ITPUB
Oct 12, 2021 · Databases

How to Handle Pagination After MySQL Sharding: Pitfalls and Solutions

When a MySQL table is sharded into multiple databases or tables, the usual LIMIT offset, pagesize pagination breaks, and this article examines why simple merge fails, then presents three practical approaches—global limit, secondary queries, and jump‑page restriction—highlighting their trade‑offs and limitations.

MySQLPerformanceSQL
0 likes · 13 min read
How to Handle Pagination After MySQL Sharding: Pitfalls and Solutions
Xiao Lou's Tech Notes
Xiao Lou's Tech Notes
Oct 12, 2021 · Databases

Optimizing ORDER BY/LIMIT in Sharded Databases with Cobar’s Algorithm

This article explains Cobar’s sharding middleware and presents an optimization technique for handling ORDER BY and LIMIT queries across multiple databases, detailing the original approach, its inefficiencies with deep pagination, the step‑by‑step improved algorithm, performance analysis, limitations, and practical applicability.

CobarLIMITORDER BY
0 likes · 8 min read
Optimizing ORDER BY/LIMIT in Sharded Databases with Cobar’s Algorithm
dbaplus Community
dbaplus Community
Sep 7, 2021 · Operations

How Ant’s Logic Data Center (LDC) Scales to 580,000 TPS on Double‑11

The article explains how Ant Group’s Logic Data Center (LDC) architecture evolved from monolithic to unit‑based distributed design, using zones, sharding, and read‑write separation to sustain a record 583,000 transactions per second during the Double‑11 shopping festival.

Distributed ArchitectureLDCLogic Data Center
0 likes · 11 min read
How Ant’s Logic Data Center (LDC) Scales to 580,000 TPS on Double‑11
Java Architecture Diary
Java Architecture Diary
Sep 2, 2021 · Backend Development

Master MyBatis‑Mate: Dictionary Binding, Encryption, Sharding & Data Scope Explained

This guide introduces MyBatis‑Mate’s core capabilities—including dictionary binding, field encryption, data masking, automatic DDL maintenance, dynamic sharding, and data‑scope permissions—while providing Maven dependencies and complete Java code examples for integrating these features into Spring Boot applications.

BackendData PermissionJava
0 likes · 8 min read
Master MyBatis‑Mate: Dictionary Binding, Encryption, Sharding & Data Scope Explained
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Aug 31, 2021 · Operations

Facebook’s Shard Manager: Strategies for Large‑Scale System Sharding, Fault Tolerance, and Resource Utilization

The article explains how Facebook’s Shard Manager tackles large‑scale system sharding by combining stateful and stateless service deployment, consistent hashing versus sharding, fault‑as‑normal principles, replication, automated failover, load‑balancing, and elastic scaling to achieve high availability and efficient resource use.

FacebookResource Utilizationload balancing
0 likes · 9 min read
Facebook’s Shard Manager: Strategies for Large‑Scale System Sharding, Fault Tolerance, and Resource Utilization
Ctrip Technology
Ctrip Technology
Aug 17, 2021 · Databases

Sharding and Database Refactoring for High‑Volume Train Ticket Orders at Ctrip

This article describes how Ctrip's senior backend engineer designed and implemented horizontal database sharding, a service‑level proxy, dual‑read/write mechanisms, and a staged migration process to overcome order‑database bottlenecks, improve scalability, and ensure high availability for the rapidly growing international train‑ticket business.

Backendhigh availabilitymiddleware
0 likes · 16 min read
Sharding and Database Refactoring for High‑Volume Train Ticket Orders at Ctrip
IT Architects Alliance
IT Architects Alliance
Aug 15, 2021 · Databases

Design Principles of 58.com Database Architecture and Codd's Twelve Rules

This article outlines 58.com’s database architecture strategies—including high availability via replication and dual‑master setups, read‑performance enhancements through indexing, read replicas, and caching, consistency solutions, scalability techniques, horizontal sharding patterns, and a review of Codd’s twelve relational rules as design guidelines.

Codd Rulesdatabase architecturesharding
0 likes · 14 min read
Design Principles of 58.com Database Architecture and Codd's Twelve Rules
21CTO
21CTO
Aug 14, 2021 · Backend Development

Designing a System That Scales to 100 Million Users: Key Strategies

This guide explains how to build a highly available, scalable architecture for supporting hundreds of millions of users, covering decoupling, redundancy, vertical and horizontal scaling, load balancing, database replication, sharding, caching, CDN, GeoDNS, and best practices for progressive system expansion.

CDNCachingDatabase Replication
0 likes · 19 min read
Designing a System That Scales to 100 Million Users: Key Strategies
Top Architect
Top Architect
Aug 14, 2021 · Big Data

Elasticsearch Overview: Architecture, Core Concepts, and Performance Optimization

This article provides a comprehensive introduction to Elasticsearch, covering its underlying Lucene-based inverted index, data types, shard routing, cluster roles, discovery mechanisms, refresh and translog handling, segment merging, and practical performance and JVM tuning tips for building scalable, near‑real‑time search systems.

ElasticsearchIndexingperformance tuning
0 likes · 35 min read
Elasticsearch Overview: Architecture, Core Concepts, and Performance Optimization
Java Architecture Diary
Java Architecture Diary
Aug 11, 2021 · Operations

Unlock Loki v2.3.0: Custom Retention, Deletion & Recording Rules Explained

Version 2.3.0 of Loki introduces enhanced features such as per‑tenant custom retention policies, time‑range log deletion via the Compactor API, Prometheus‑style recording rules, a new pattern parser for LogQL, ingestion sharding for faster queries, and advanced IP‑matching syntax, all aimed at improving storage efficiency, compliance, and observability.

Log ManagementLogQLLoki
0 likes · 9 min read
Unlock Loki v2.3.0: Custom Retention, Deletion & Recording Rules Explained
Open Source Linux
Open Source Linux
Aug 8, 2021 · Databases

MongoDB Essentials: 52 Common Questions Answered

This comprehensive guide covers everything from MongoDB's core concepts, data model, and architecture to practical commands for creating databases, collections, indexes, sharding, replication, aggregation, and troubleshooting, providing clear answers to over fifty frequently asked questions.

AggregationMongoDBNoSQL
0 likes · 27 min read
MongoDB Essentials: 52 Common Questions Answered
MaGe Linux Operations
MaGe Linux Operations
Aug 4, 2021 · Databases

What Is MongoDB? Features, Commands, and Best Practices Explained

This article provides a comprehensive overview of MongoDB, covering its definition, document‑oriented storage, key features, differences from relational databases, sharding and replication mechanisms, common commands, data types, indexing, aggregation, and practical usage scenarios for modern applications.

AggregationMongoDBNoSQL
0 likes · 23 min read
What Is MongoDB? Features, Commands, and Best Practices Explained
Programmer DD
Programmer DD
Aug 3, 2021 · Databases

Why MySQL Uses B+ Trees for Indexes and How to Design Effective Indexes

This article explains why MySQL chooses B+ trees for its indexes, covers the left‑most prefix rule for composite indexes, offers practical index‑design tips, discusses MyBatis caching, master‑slave replication, and sharding strategies for large‑scale databases.

B+ TreeDatabase OptimizationMyBatis
0 likes · 10 min read
Why MySQL Uses B+ Trees for Indexes and How to Design Effective Indexes
Java Architecture Diary
Java Architecture Diary
Jul 28, 2021 · Backend Development

Unlock Enterprise‑Level Data Handling with MyBatis‑Mate 1.0.1: Features & Code Guide

The release of MyBatis‑Mate 1.0.1 introduces enterprise‑grade features such as dictionary binding, field encryption, data desensitization, automatic DDL maintenance, and dynamic multi‑datasource sharding, accompanied by code examples, future roadmap, and Maven dependencies for seamless integration into Spring Boot projects.

BackendDDLDictionary Binding
0 likes · 7 min read
Unlock Enterprise‑Level Data Handling with MyBatis‑Mate 1.0.1: Features & Code Guide
IT Architects Alliance
IT Architects Alliance
Jul 26, 2021 · Databases

How to Diagnose and Fix Database IO/CPU Bottlenecks with Sharding

The article explains how IO and CPU bottlenecks increase active database connections, then details horizontal and vertical sharding techniques, practical tools, step‑by‑step implementation, and common pitfalls to help engineers relieve pressure on database resources.

CPU bottleneckHorizontal PartitionIO bottleneck
0 likes · 10 min read
How to Diagnose and Fix Database IO/CPU Bottlenecks with Sharding
Programmer DD
Programmer DD
Jul 22, 2021 · Backend Development

Boost Spring Boot Scheduled Tasks with Elastic Job Sharding

This tutorial explains how to use Elastic Job's sharding configuration in Spring Boot to accelerate scheduled task execution, improve resource utilization, and achieve high‑availability by distributing work across multiple job instances.

Elastic-JobSpring Bootbackend development
0 likes · 8 min read
Boost Spring Boot Scheduled Tasks with Elastic Job Sharding
IT Architects Alliance
IT Architects Alliance
Jul 6, 2021 · Databases

58.com Database Architecture Design Overview

This article presents a comprehensive overview of 58.com’s database architecture, covering availability through replication and dual‑master setups, read‑performance enhancements via indexing, replicas and caching, consistency strategies, rapid horizontal scaling, sharding patterns, and practical SQL considerations alongside Codd’s 12 relational rules.

Cachingdatabase architecturesharding
0 likes · 11 min read
58.com Database Architecture Design Overview
Java Architect Essentials
Java Architect Essentials
Jun 21, 2021 · Databases

Understanding MySQL Slow Queries, Index Optimization, and Integration with Elasticsearch and HBase

This article explains why MySQL queries become slow, how index design and common pitfalls affect performance, introduces MDL locks and large‑table strategies, then compares Elasticsearch and HBase as complementary storage and search solutions, providing practical code examples and best‑practice recommendations.

Database OptimizationHBaseIndexing
0 likes · 16 min read
Understanding MySQL Slow Queries, Index Optimization, and Integration with Elasticsearch and HBase
Top Architect
Top Architect
Jun 16, 2021 · Databases

Understanding MySQL Memory Management and When to Shard Tables

The article explains how MySQL uses different memory areas such as Thread Memory, Sharing, and InnoDB Buffer Pool, describes the impact of large user tables on query performance, and shows that when a table size exceeds the InnoDB buffer pool capacity, sharding becomes necessary.

InnoDBLinuxMySQL
0 likes · 17 min read
Understanding MySQL Memory Management and When to Shard Tables
IT Architects Alliance
IT Architects Alliance
May 27, 2021 · Backend Development

Can Sharding Alone Scale Your Services? Exploring Unitization for Unlimited Growth

This article analyzes the typical evolution from monolithic to RPC-based services, explains why sharding and database partitioning cannot alone achieve unlimited scaling due to connection limits, and introduces a unitization approach that assigns each application to a specific database shard to overcome those constraints.

Backendscalabilityservice architecture
0 likes · 8 min read
Can Sharding Alone Scale Your Services? Exploring Unitization for Unlimited Growth
IT Architects Alliance
IT Architects Alliance
May 26, 2021 · Databases

Understanding MySQL Slow Queries, Elasticsearch, and HBase: Causes and Practical Solutions

This article explains why MySQL queries become slow, how indexes work and fail, the impact of MDL locks, large‑table challenges, sharding and read‑write splitting strategies, then introduces Elasticsearch’s search capabilities and HBase’s column‑family storage, offering practical guidance for each technology.

ElasticsearchHBaseIndexing
0 likes · 17 min read
Understanding MySQL Slow Queries, Elasticsearch, and HBase: Causes and Practical Solutions
Architect
Architect
May 26, 2021 · Backend Development

From Monolithic to Unitized Architecture: Overcoming Unlimited Scaling Limits

This article traces the evolution of backend services from monolithic applications through RPC and sharding, explains why sharding and database partitioning cannot alone achieve unlimited scaling due to connection limits, and proposes a unitization approach that isolates database connections per service to enable true horizontal expansion.

shardingunitization
0 likes · 7 min read
From Monolithic to Unitized Architecture: Overcoming Unlimited Scaling Limits
Code Ape Tech Column
Code Ape Tech Column
May 21, 2021 · Databases

Why Your MySQL Queries Are Slow and How ElasticSearch & HBase Can Help

This article analyzes common causes of slow MySQL queries such as index misuse, MDL locks, and large‑table bottlenecks, then presents practical solutions like proper indexing, sharding, read/write splitting, and evaluates when to complement MySQL with ElasticSearch or HBase for better performance.

ElasticsearchHBaseIndex Optimization
0 likes · 19 min read
Why Your MySQL Queries Are Slow and How ElasticSearch & HBase Can Help
21CTO
21CTO
May 20, 2021 · Backend Development

From Monolith to Scalable Order System: Lessons from Ele.me’s 4‑Year Evolution

Over four years at Ele.me, the author chronicles the transformation of the order platform from a single‑machine Python monolith to a distributed, sharded, message‑driven architecture, detailing challenges in scaling, performance testing, fault injection, Redis usage, and service separation that shaped today’s robust backend.

Redismessagingmicroservices
0 likes · 49 min read
From Monolith to Scalable Order System: Lessons from Ele.me’s 4‑Year Evolution
Java Interview Crash Guide
Java Interview Crash Guide
May 19, 2021 · Backend Development

How to Optimize Java Scheduled Tasks for High‑Volume Data Sync

This article explains how to optimize Java scheduled tasks for large‑scale data synchronization by introducing phased improvements such as blacklist mechanisms, multithreaded execution with CountDownLatch, and server‑level sharding, providing practical guidelines for performance and reliability.

ConcurrencyJavaPerformance Optimization
0 likes · 13 min read
How to Optimize Java Scheduled Tasks for High‑Volume Data Sync
dbaplus Community
dbaplus Community
May 17, 2021 · Databases

How Migrating from Elasticsearch to MongoDB Cut Costs 10‑Fold and Boosted Latency

This article presents a detailed case study of moving a 2‑petabyte smart‑product data workload from Elasticsearch to MongoDB, covering business background, source cluster architecture, MongoDB design and resource planning, step‑by‑step performance optimizations, latency and cost comparisons, and guidance on when each database is appropriate.

ElasticsearchMongoDBPerformance Optimization
0 likes · 21 min read
How Migrating from Elasticsearch to MongoDB Cut Costs 10‑Fold and Boosted Latency
Full-Stack Internet Architecture
Full-Stack Internet Architecture
May 12, 2021 · Databases

Database Scaling Strategies: From Single Instance to Smooth Horizontal Expansion

The article explains how to evolve a simple single‑instance database into a highly available, horizontally sharded system, detailing offline scaling, online dual‑write migration, and a smooth four‑node expansion process with configuration changes, data migration, and cleanup steps.

Database Scalingconfiguration managementhigh availability
0 likes · 6 min read
Database Scaling Strategies: From Single Instance to Smooth Horizontal Expansion
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 24, 2021 · Databases

Deep Dive into Redis Cluster Architecture and Principles

This article provides a comprehensive analysis of Redis Cluster, covering node and slot assignment, command execution, resharding, redirection, fault‑tolerance, gossip communication, scaling strategies, configuration limits, and practical code examples for building and operating a high‑availability sharded Redis deployment.

Redisclusterfailover
0 likes · 21 min read
Deep Dive into Redis Cluster Architecture and Principles
Top Architect
Top Architect
Apr 19, 2021 · Databases

Understanding MySQL Index Structures, B+ Trees, and Practical Optimization Techniques

This article explains why MySQL uses B+‑tree indexes, describes the left‑most prefix rule for composite indexes, offers practical index‑design and optimization tips, outlines MyBatis first‑ and second‑level caching, details master‑slave replication, and introduces common sharding strategies and their implementation considerations.

B+ TreeDatabase OptimizationMyBatis
0 likes · 12 min read
Understanding MySQL Index Structures, B+ Trees, and Practical Optimization Techniques
Wukong Talks Architecture
Wukong Talks Architecture
Apr 6, 2021 · Databases

When and How to Apply Database Sharding (Split Database and Tables)

This article explains the signs that indicate a need for database sharding, outlines performance bottlenecks, presents optimization techniques such as SQL tuning, table redesign, read‑write separation, and then details vertical and horizontal splitting strategies, their implementation across single or multiple databases, and the added complexities like cross‑database joins, distributed transactions, and ID generation.

scalabilitysharding
0 likes · 12 min read
When and How to Apply Database Sharding (Split Database and Tables)
ITPUB
ITPUB
Apr 2, 2021 · Databases

Choosing the Right MySQL Architecture: Master‑Standby, Dual‑Master, and Consistency Strategies

This article examines core MySQL architecture principles—high availability, performance, consistency, and scalability—then compares four common deployment patterns, analyzes their trade‑offs, and presents practical consistency solutions for both master‑slave replication and cache synchronization, ending with personal insights on evolution and sharding.

MySQLRead-Write Separationconsistency
0 likes · 12 min read
Choosing the Right MySQL Architecture: Master‑Standby, Dual‑Master, and Consistency Strategies
Architects Research Society
Architects Research Society
Mar 29, 2021 · Operations

eBay’s Scalability Best Practices: Functional Partitioning, Horizontal Sharding, Asynchronous Decoupling, and More

The article outlines eBay’s practical scalability principles—including functional partitioning, horizontal sharding, avoiding distributed transactions, aggressive asynchronous decoupling, moving work to async pipelines, virtualization, and intelligent caching—demonstrating how large‑scale web systems can be designed for linear growth and high availability.

Cachingasynchronousdistributed systems
0 likes · 14 min read
eBay’s Scalability Best Practices: Functional Partitioning, Horizontal Sharding, Asynchronous Decoupling, and More
Ctrip Technology
Ctrip Technology
Mar 18, 2021 · Backend Development

Design and Implementation of Ctrip's Unified Accounting Platform

This article presents a comprehensive case study of Ctrip's unified accounting platform, detailing its evolution from legacy systems, architectural redesign, component decomposition, logging, sharding, asynchronous processing, database strategies, exception handling, and daily settlement mechanisms to achieve agility, decoupling, and reusability.

Backendaccounting platformlogging
0 likes · 16 min read
Design and Implementation of Ctrip's Unified Accounting Platform
dbaplus Community
dbaplus Community
Mar 14, 2021 · Databases

How Vivo Built a Scalable Comment Platform with MongoDB Sharding

This article explains how Vivo designed a company‑wide comment middle‑platform, chose MySQL and MongoDB, deep‑dived into MongoDB cluster architecture, shard key strategies, and practical solutions for scaling, migration, and high availability in a high‑traffic environment.

MongoDBcomment systemdatabase design
0 likes · 11 min read
How Vivo Built a Scalable Comment Platform with MongoDB Sharding
Sohu Tech Products
Sohu Tech Products
Mar 10, 2021 · Databases

Elasticsearch Deployment Best Practices: Memory, CPU, Sharding, Replicas, Hot/Warm Architecture, Node Roles, Monitoring and Troubleshooting

This article presents practical best‑practice guidelines for configuring Elasticsearch in production, covering heap memory sizing, CPU considerations, shard and replica planning, hot‑warm node architecture, node role settings, common pitfalls, monitoring APIs, and troubleshooting tips.

ElasticsearchNode Rolescluster tuning
0 likes · 15 min read
Elasticsearch Deployment Best Practices: Memory, CPU, Sharding, Replicas, Hot/Warm Architecture, Node Roles, Monitoring and Troubleshooting
IT Architects Alliance
IT Architects Alliance
Mar 7, 2021 · Databases

Mastering Distributed Transactions: From ACID to TCC and Sharding Strategies

This article provides a comprehensive technical guide to distributed transactions, covering ACID fundamentals, consistency models, sharding techniques, CAP and BASE theories, and detailed implementations of two‑phase, three‑phase, and TCC protocols, while highlighting their advantages, limitations, and practical considerations.

BASE theoryCAP theoremTCC
0 likes · 23 min read
Mastering Distributed Transactions: From ACID to TCC and Sharding Strategies
JD Cloud Developers
JD Cloud Developers
Mar 5, 2021 · Databases

How Transparent Sharding Middleware Powers NewSQL: Core Functions Explained

This article explains the fundamentals of transparent sharding middleware in NewSQL systems, covering data partitioning strategies, read/write separation, the complete SQL processing pipeline, protocol adaptation for MySQL/PostgreSQL, distributed transaction models such as XA, Saga and TCC, and essential database governance and online scaling techniques.

Database GovernanceDatabase MiddlewareNewSQL
0 likes · 28 min read
How Transparent Sharding Middleware Powers NewSQL: Core Functions Explained
Amap Tech
Amap Tech
Mar 5, 2021 · Databases

Scaling and Migrating a High‑Volume Order System with Sharding, Data Synchronization and Gray‑Rollout on Alibaba Cloud

To support Gaode Taxi’s soaring order volume, the team expanded from four to eight ECS instances, re‑sharded 256 tables into 4,096, built a custom binlog‑to‑Kafka sync middleware for full‑load and incremental migration, implemented rigorous validation and repair processes, and employed a gray‑rollout with ABC verification, completing the migration without code changes or incidents.

Alibaba CloudCapacity Planningdata synchronization
0 likes · 16 min read
Scaling and Migrating a High‑Volume Order System with Sharding, Data Synchronization and Gray‑Rollout on Alibaba Cloud
ITPUB
ITPUB
Mar 1, 2021 · Databases

Designing a Scalable Comment Service: Vivo’s MongoDB Architecture Deep Dive

This article details Vivo's journey in building a company‑wide comment platform, explaining why MongoDB was chosen over MySQL, how its sharded cluster is structured, the challenges of shard‑key selection, and the practical steps taken to scale and maintain the system.

MongoDBcluster architecturecomment system
0 likes · 10 min read
Designing a Scalable Comment Service: Vivo’s MongoDB Architecture Deep Dive
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 1, 2021 · Databases

How We Scaled a High‑Volume Order System: Sharding, Migration, and Zero‑Downtime Strategies

This article details the end‑to‑end process of expanding a high‑traffic ride‑hailing order system on Alibaba Cloud, covering capacity planning, database sharding from 256 to 4096 tables, custom data‑sync middleware, validation, repair, and a gray‑release migration that achieved zero incidents.

capacity-planningcloud-computingdata migration
0 likes · 17 min read
How We Scaled a High‑Volume Order System: Sharding, Migration, and Zero‑Downtime Strategies
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 24, 2021 · Big Data

Gairos: Uber’s Real‑Time Data Processing, Storage and Query Platform and Its Scalability Optimizations

The article describes Uber’s Gairos platform—a unified real‑time data ingestion, storage, and query system built on Kafka, Elasticsearch and RT‑Gairos—detailing its architecture, Uber use cases such as dynamic pricing, the scalability and reliability challenges faced, and the suite of optimization techniques (sharding, query routing, caching, index merging, template tuning, and data‑pruning) applied to achieve low latency and high throughput.

ElasticsearchReal-time DataUber
0 likes · 26 min read
Gairos: Uber’s Real‑Time Data Processing, Storage and Query Platform and Its Scalability Optimizations
Architects' Tech Alliance
Architects' Tech Alliance
Feb 4, 2021 · Databases

What Makes NewSQL Databases Advanced? A Comparative Analysis with Middleware‑Based Sharding

This article objectively compares NewSQL distributed databases with traditional middleware‑plus‑sharding solutions, examining architecture, distributed transactions, CAP constraints, high‑availability, scaling, storage engines, maturity, and practical adoption scenarios to help readers decide which approach best fits their needs.

NewSQLTransactional Consistencydistributed databases
0 likes · 17 min read
What Makes NewSQL Databases Advanced? A Comparative Analysis with Middleware‑Based Sharding
Architecture Digest
Architecture Digest
Feb 1, 2021 · Databases

Comparing NewSQL Distributed Databases with Middleware‑Based Sharding: Advantages, Trade‑offs, and Application Scenarios

This article objectively compares NewSQL distributed databases with traditional middleware‑plus‑sharding solutions, examining their architectural differences, distributed transaction handling, high‑availability mechanisms, scaling and sharding strategies, SQL support, storage engines, and maturity to help practitioners decide which approach best fits their workload and operational constraints.

NewSQLdatabase architecturehigh availability
0 likes · 17 min read
Comparing NewSQL Distributed Databases with Middleware‑Based Sharding: Advantages, Trade‑offs, and Application Scenarios
Top Architect
Top Architect
Jan 22, 2021 · Databases

Debunking Common MongoDB Myths: A Comprehensive Guide

This article systematically refutes ten widespread misconceptions about MongoDB—covering scalability, versioning, data format, transactions, relationships, sharding, security, data loss, and suitability—while explaining its architecture, BSON storage, and best‑practice usage with illustrative code examples.

BSONMongoDBNoSQL
0 likes · 14 min read
Debunking Common MongoDB Myths: A Comprehensive Guide
Java Backend Technology
Java Backend Technology
Jan 14, 2021 · Databases

How to Overcome Database Bottlenecks with Sharding and Scaling Strategies

This article explains common I/O and CPU bottlenecks in databases, introduces horizontal and vertical sharding techniques, discusses tools, global primary‑key generation methods, Snowflake ID algorithm, migration challenges, and provides practical guidance on when and how to apply database partitioning to improve performance and scalability.

Snowflakedatabaseglobal ID
0 likes · 16 min read
How to Overcome Database Bottlenecks with Sharding and Scaling Strategies
Programmer DD
Programmer DD
Jan 12, 2021 · Databases

NewSQL vs Sharding: Which Database Architecture Truly Wins?

This article objectively compares NewSQL distributed databases with middleware‑based sharding solutions, examining their architectural differences, distributed transaction handling, high‑availability mechanisms, scaling and sharding strategies, SQL support, storage engines, and overall maturity to help readers decide which approach best fits their workload.

NewSQLdistributed databaseshigh availability
0 likes · 21 min read
NewSQL vs Sharding: Which Database Architecture Truly Wins?
JD Retail Technology
JD Retail Technology
Jan 4, 2021 · Backend Development

Evolution of the PLUS Membership Partner System Architecture: Design Patterns, Sharding, and Cluster Separation

This article describes how the PLUS membership partner platform evolved from a simple initial design to a mature, high‑performance backend architecture by applying command, template, and strategy patterns, sharding‑JDBC, cluster separation, and Spring AOP for monitoring and exception handling.

cluster separationshardingsystem architecture
0 likes · 8 min read
Evolution of the PLUS Membership Partner System Architecture: Design Patterns, Sharding, and Cluster Separation
Java Architect Essentials
Java Architect Essentials
Dec 31, 2020 · Databases

MySQL Single Table Optimization, Sharding, Partitioning, and Scaling Techniques

When a MySQL table grows large, performance degrades sharply, so this guide explains single‑table tuning, proper field choices, index strategies, query best practices, engine differences, system parameters, hardware upgrades, read‑write splitting, caching layers, table partitioning, vertical and horizontal sharding, and how to choose suitable sharding solutions.

DatabaseScalingIndexingMySQL
0 likes · 25 min read
MySQL Single Table Optimization, Sharding, Partitioning, and Scaling Techniques
Liangxu Linux
Liangxu Linux
Dec 26, 2020 · Databases

Master MySQL Performance: Practical Soft and Hard Optimization Techniques

This guide explains how to boost MySQL performance through soft optimizations like query analysis, index usage, and table restructuring, as well as hard optimizations involving hardware upgrades, configuration tuning, sharding, read‑write splitting, and cache clustering.

Database OptimizationIndexingMySQL
0 likes · 8 min read
Master MySQL Performance: Practical Soft and Hard Optimization Techniques
Tencent Cloud Developer
Tencent Cloud Developer
Dec 24, 2020 · Big Data

Distributed Search Engine Design and Index Management in WeChat Search

The article details WeChat Search’s practical distributed architecture—using a Chubby‑elected leader for shard‑to‑node mapping, hash‑based sharding with dynamic rebalancing, a Lambda‑style batch and near‑real‑time indexing pipeline, relaxed monotonic consistency, and group‑based searcher scaling—to illustrate trade‑offs and lessons for building scalable, reliable search services.

LSMLambda Architecturedistributed systems
0 likes · 28 min read
Distributed Search Engine Design and Index Management in WeChat Search
vivo Internet Technology
vivo Internet Technology
Dec 23, 2020 · Backend Development

How Vivo Scaled Its Order System: Sharding, Migration, and Real‑World Lessons

This article details how Vivo transformed its monolithic e‑commerce order service into a scalable, service‑oriented system by applying data archiving, sharding‑JDBC based sharding, MySQL‑to‑Elasticsearch sync, zero‑downtime migration, and distributed‑transaction techniques, while sharing practical pitfalls and performance results.

Database ScalingElasticsearchMySQL
0 likes · 17 min read
How Vivo Scaled Its Order System: Sharding, Migration, and Real‑World Lessons
Java Interview Crash Guide
Java Interview Crash Guide
Dec 17, 2020 · Databases

Mastering Data Sharding: When and How to Split Your Database

This article explains the concepts, types, advantages, and drawbacks of vertical and horizontal database sharding, discusses the challenges such as distributed transactions, cross‑node joins, pagination, global primary‑key generation, migration, and provides practical guidelines and case studies for deciding when and how to apply sharding.

Horizontal ShardingVertical Shardingdatabase partitioning
0 likes · 28 min read
Mastering Data Sharding: When and How to Split Your Database
Laravel Tech Community
Laravel Tech Community
Dec 10, 2020 · Databases

MySQL Single‑Table Optimization, Partitioning, Sharding and Scaling Strategies

This article provides a comprehensive guide to improving MySQL performance by optimizing single‑table schemas, indexes, queries, engine settings, system parameters, and then discusses read/write separation, caching layers, table partitioning, vertical and horizontal sharding, compatible scalable databases and when to consider NoSQL alternatives.

Database OptimizationMySQLPartitioning
0 likes · 21 min read
MySQL Single‑Table Optimization, Partitioning, Sharding and Scaling Strategies
dbaplus Community
dbaplus Community
Dec 6, 2020 · Databases

Sharding Massive MySQL Tables: End‑to‑End Architecture, Migration & Best Practices

This article presents a comprehensive, step‑by‑step case study of a large‑scale MySQL sharding project, covering business refactoring, storage architecture design, data migration, synchronization strategies, capacity planning, validation, rollout procedures, stability safeguards, and cross‑team collaboration.

MySQLdatabase architecturesharding
0 likes · 28 min read
Sharding Massive MySQL Tables: End‑to‑End Architecture, Migration & Best Practices
Senior Brother's Insights
Senior Brother's Insights
Dec 2, 2020 · Databases

Mastering Data Sharding: When, How, and What to Watch Out For

This comprehensive guide explains why and when to split relational databases, details vertical and horizontal sharding techniques, discusses associated challenges such as distributed transactions, cross‑node joins, pagination, global primary keys, and offers practical solutions and middleware options.

Global ID GenerationHorizontal ShardingVertical Sharding
0 likes · 24 min read
Mastering Data Sharding: When, How, and What to Watch Out For
ITPUB
ITPUB
Nov 12, 2020 · Databases

How Vivo Scaled to Billions of Records: Sharding and InnoDB Compression Strategies

This article details how Vivo's cloud service tackled explosive data growth by applying horizontal and vertical sharding, routing‑table based dynamic expansion, and MySQL InnoDB compression, providing step‑by‑step guidance, performance results, and practical recommendations for large‑scale database deployments.

Database ScalingInnoDBMySQL
0 likes · 16 min read
How Vivo Scaled to Billions of Records: Sharding and InnoDB Compression Strategies
Practical DevOps Architecture
Practical DevOps Architecture
Nov 10, 2020 · Databases

Design of Ant Financial's Logical Data Center (LDC) and Unitization for High‑TPS Payments

The article explains how Ant Financial’s Logical Data Center (LDC) and unit‑based architecture, combined with sharding, CAP analysis, and OceanBase’s Paxos‑based consensus, enable the payment platform to sustain tens of millions of transactions per second during Double‑11 events while ensuring high availability and disaster recovery.

CAP theoremHigh TPSOceanBase
0 likes · 42 min read
Design of Ant Financial's Logical Data Center (LDC) and Unitization for High‑TPS Payments
Architect
Architect
Oct 27, 2020 · Databases

Database Bottlenecks and Sharding: Strategies for Horizontal and Vertical Partitioning

This article examines common database performance bottlenecks such as I/O and CPU limits, explains the concepts, results, and scenarios of horizontal and vertical sharding—including database and table partitioning—and outlines tools, steps, and challenges for implementing effective sharding solutions.

databaseshorizontal-partitioningsharding
0 likes · 11 min read
Database Bottlenecks and Sharding: Strategies for Horizontal and Vertical Partitioning
Top Architect
Top Architect
Oct 20, 2020 · Databases

Database Bottlenecks and Sharding Strategies

This article analyzes common database performance bottlenecks such as I/O and CPU limits, explains how horizontal and vertical sharding (including database and table partitioning) can alleviate these issues, introduces practical tools and step‑by‑step implementation guidance, and discusses related challenges like non‑partition key queries and scaling.

Horizontal PartitioningVertical Partitioningdatabases
0 likes · 8 min read
Database Bottlenecks and Sharding Strategies
JD Cloud Developers
JD Cloud Developers
Oct 14, 2020 · Databases

How ClickHouse Distributed Tables Write Data: Sync vs Async Explained

This article dissects ClickHouse's Distributed table write path, detailing how the Distributed engine creates tables, decides between synchronous and asynchronous insertion, manages local and remote shards, handles sharding keys, and ensures atomic data distribution across the cluster.

ClickHouseData InsertionDistributed Table
0 likes · 14 min read
How ClickHouse Distributed Tables Write Data: Sync vs Async Explained
macrozheng
macrozheng
Oct 9, 2020 · Databases

How to Implement Database Sharding: Horizontal & Vertical Partitioning with Sharding-JDBC

This article explains the fundamentals of database sharding, covering both vertical and horizontal partitioning concepts, routing algorithms, advantages and drawbacks, practical implementation steps using sharding-jdbc, and discusses related challenges such as distributed transactions, pagination, global IDs, and tool selection.

JavaVertical Scalingdatabase partitioning
0 likes · 17 min read
How to Implement Database Sharding: Horizontal & Vertical Partitioning with Sharding-JDBC
Wukong Talks Architecture
Wukong Talks Architecture
Sep 24, 2020 · Fundamentals

Common Pitfalls in Distributed Systems: Message Queues, Caches, Sharding, and Transactions

This article systematically explains the fundamental concepts and typical pitfalls of distributed systems—including CAP and BASE theories, message‑queue reliability issues, distributed cache challenges, sharding strategies, and transaction models—while offering practical mitigation techniques for each problem.

CAP theoremdistributed systemsdistributed transaction
0 likes · 24 min read
Common Pitfalls in Distributed Systems: Message Queues, Caches, Sharding, and Transactions
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Sep 20, 2020 · Databases

Database Read/Write Separation: Principles, Advantages, Disadvantages, and Implementation Strategies

Database read/write separation, alongside sharding and master‑slave architectures, mitigates high‑concurrency bottlenecks by distributing reads to replicas and writes to a primary, offering scalability and performance benefits while introducing challenges such as replication lag, routing complexity, and resource utilization trade‑offs.

High ConcurrencyMaster‑SlavePerformance
0 likes · 10 min read
Database Read/Write Separation: Principles, Advantages, Disadvantages, and Implementation Strategies
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Sep 17, 2020 · Fundamentals

Why Distributed Systems Matter: Core Concepts, Design Trade‑offs & CAP

This article explores the fundamentals of distributed systems, explaining what they are, why they’re used, design considerations such as replication and partitioning, the implications of the CAP theorem, common distribution strategies, typical architectural patterns, and the advantages and challenges of building and operating such systems.

CAP theoremSystem Designdistributed systems
0 likes · 14 min read
Why Distributed Systems Matter: Core Concepts, Design Trade‑offs & CAP
Architecture Digest
Architecture Digest
Sep 14, 2020 · Databases

Understanding the Underlying Mechanics of Elasticsearch and Lucene

This article provides a comprehensive, top‑down and bottom‑up explanation of Elasticsearch’s internal architecture, covering clusters, nodes, shards, Lucene segments, inverted indexes, stored fields, document values, caching, merging, routing, scaling, and query processing, while addressing common performance questions.

CachingElasticsearchLucene
0 likes · 11 min read
Understanding the Underlying Mechanics of Elasticsearch and Lucene
IT Xianyu
IT Xianyu
Sep 11, 2020 · Backend Development

Beyond Sharding: Unitization as a Solution to Unlimited Service Scaling

The article examines why traditional sharding and database partitioning cannot alone achieve limitless scaling, explains the problem of excessive RPC‑to‑DB connections, and proposes a unitization approach that limits each service to a single database shard to enable true horizontal expansion.

Database Connectionsscalabilitysharding
0 likes · 8 min read
Beyond Sharding: Unitization as a Solution to Unlimited Service Scaling
JavaEdge
JavaEdge
Sep 8, 2020 · Databases

Understanding Redis Sharding: Benefits, Strategies, and Implementation

This article explains Redis sharding, covering its purpose, various partitioning methods such as range and hash partitioning, implementation approaches like client‑side and proxy‑assisted sharding, their drawbacks, and practical steps for migration and using Redis Cluster or Twemproxy.

PartitioningProxyRedis
0 likes · 9 min read
Understanding Redis Sharding: Benefits, Strategies, and Implementation
Java Backend Technology
Java Backend Technology
Aug 30, 2020 · Databases

Mastering Database Sharding: Core Concepts, Middleware, and Common Challenges

Sharding splits a single database into multiple servers to improve performance, covering vertical and horizontal partitioning, middleware options, and key challenges such as distributed transactions, cross‑node joins, ID generation, pagination, routing transparency, and choosing between frameworks or custom solutions.

database partitioningdistributed transactionsid generation
0 likes · 16 min read
Mastering Database Sharding: Core Concepts, Middleware, and Common Challenges