This article provides a comprehensive overview of Oracle's database products, explaining why they matter, detailing the physical and logical storage structures, instance processes and memory areas, and tracing the evolution from early versions through RAC, multitenancy, and the latest 18c features.
This article chronicles the architectural evolution of JD Baitiao’s backend—from early MySQL monoliths through Solr‑HBase, MongoDB, and DBRep—to the adoption of Apache ShardingSphere, highlighting the motivations, technical trade‑offs, decoupling strategies, and performance outcomes for a high‑throughput financial service.
This article explains the complete MySQL execution pipeline—from client connection, authentication, and permission checks through caching, parsing, optimization, and execution—plus the logical order of SQL clauses, illustrated with diagrams to help developers optimize and comprehend database queries.
This article explains Redis's original single‑threaded event‑driven design, the problems it causes, how the Lazy Free mechanism and asynchronous deletion were introduced in Redis 4.0, and how Redis 6.0 adds multi‑threaded I/O while discussing its limitations and comparing it with Tair's approach.
This article describes how TAL Education Group evaluated, selected, and customized the open‑source Orchestrator tool to build a highly available, secure, and extensible MySQL HA solution that meets 99.99% uptime, data‑integrity, cross‑datacenter, and operational automation requirements.
This article outlines the motivation and seven fundamental aspects of distributed storage—replication, storage engine, transactions, analytics, multi‑core processing, computation, and compilation—detailing their roles, challenges, and design considerations for building scalable, reliable, and high‑performance data systems.
This article outlines seven fundamental aspects of distributed storage—replication, storage engine, transactions, analysis, multi‑core processing, computation, and compilation—explaining their roles, challenges, and design considerations for building scalable, reliable, and high‑performance storage systems.
This article explains the concepts of ClickHouse local and distributed tables, why writing directly to distributed tables can be problematic, and how replication, sharding, and the ReplicatedMergeTree engine work together with ZooKeeper to provide high‑availability and scalable query processing.
In distributed databases, proxies must merge sorted results from multiple shards, but large result sets exceed memory limits; the article proposes a batch‑fetching approach using per‑shard sort buffers and a priority‑queue merge, eliminating disk I/O and reducing network waste while preserving global order.
This article explains TiDB's HTAP architecture, covering industry challenges, the row‑store TiKV and column‑store TiFlash design, MPP integration in TiDB 5.0, and a range of real‑time use cases such as dashboards, reporting, and data‑warehouse pipelines.
The article walks through the challenges of growing data volumes, compares master‑slave, vertical, horizontal, and sharding‑plus‑partitioning architectures, explains their pros and cons, and provides concrete guidance on selecting and implementing a suitable database solution, including middleware options and real‑world case studies.
This article explains MySQL's three‑layer logical architecture, the roles of binary log, redo log, and undo log, how they interact during data updates, and the configuration options that affect durability and performance.
This article reviews Tencent Cloud’s self‑developed MySQL kernel TXSQL, detailing its enterprise‑grade features, evolutionary roadmap, overall and cloud‑native TDSQL‑C architecture, columnar engine for OLAP, instant DDL capabilities, high‑availability mechanisms, performance optimizations, and the rigorous development and release process that underpins its stability.
The article details how China Construction Bank's fintech arm designed, deployed, and operated a cloud‑native, three‑layer MPP data warehouse spanning 16,000 servers, covering architectural choices, performance gains, operational automation, and high‑availability strategies for ultra‑large scale workloads.
This article explains microservice fundamentals, outlines their advantages, and dives deep into data‑design considerations such as one‑database‑per‑service, polyglot persistence versus multi‑model databases, and why MongoDB’s dynamic schema, change streams, and sharding make it a strong fit for scalable microservice architectures.
The article explains how Redis read/write separation works, compares star and chain replication architectures, and highlights the benefits of transparent compatibility, high availability, and improved performance for read‑heavy, write‑light workloads.
This article explains the architecture of Alibaba Cloud RDS MySQL three‑node enterprise edition, detailing the X‑Paxos consensus protocol, node roles, election mechanisms, weight‑based leader selection, state‑machine diagnostics, disk health probing, and reverse‑heartbeat design that together provide a robust high‑availability database solution.
This article provides a comprehensive overview of MySQL, detailing its configuration file search order, component architecture, various storage engines such as MyISAM, NDB, Memory, and an in‑depth examination of InnoDB’s internal structures, memory management, background threads, LRU handling, redo log buffering, and checkpoint mechanisms.
This article presents a technical case study of Yiche’s 818 Car Carnival data dashboard, detailing the background, business requirements, TiDB selection and architecture, encountered issues with TiDB, TiCDC and query performance, and the solutions and performance results achieved.
This article explains Redis’s overall architecture, covering its data model, supported value types, operation interfaces, memory versus disk storage choices, access pattern selection, I/O threading models, indexing mechanisms, specific CRUD logic, and persistence strategies, helping readers grasp both high‑level design and detailed implementation.
TiDB is a distributed, MySQL-compatible database built from three core components—TiDB Server for stateless SQL processing, PD for global scheduling and metadata management, and TiKV for high‑performance key‑value storage—coordinated via the Raft consensus algorithm to ensure strong consistency and fault tolerance.
This article compares MySQL and HBase by examining their architectural designs, storage engines (B‑Tree vs LSM‑Tree), performance characteristics, ecosystem features such as TTL and multi‑versioning, and identifies scenarios where HBase is a suitable complement to MySQL for large‑scale data workloads.
This article compares MySQL and HBase across architecture, engine design, indexing structures, and feature sets such as TTL and multi‑versioning, highlighting how MySQL excels in low‑latency online transactions while HBase offers distributed scalability and write‑optimized storage for big‑data scenarios.
NetBank’s database deployment has evolved from a simple two‑site three‑center disaster‑recovery model to a sophisticated three‑site five‑center architecture, incorporating distributed databases, multi‑tenant isolation, transaction consistency, latency optimization, and containerized deployment to achieve high availability, scalability, and cost efficiency.
This article presents the architecture, key features, and operational benefits of a cloud‑native ClickHouse OLAP platform, describing how storage‑compute separation, a unified master node, and shared storage reduce cost, improve availability, and simplify management while remaining fully compatible with the open‑source ClickHouse ecosystem.
This article explains the principles of master‑slave read/write separation, the MySQL binlog‑based replication process, its side effects, practical ways to mitigate replication lag, and how middleware or proxy layers can simplify database access in high‑concurrency environments.
Shopee’s Logistics Channel Service migrated from a shared‑cluster MySQL setup to dedicated clusters, added TiDB for transient tracking data, and ultimately adopted hash‑based sharding with separate order and tracking services plus an asynchronous compensation mechanism, enabling uniform data distribution, cross‑database consistency, six‑month archiving, and scalable growth without rebalancing.
This article explains MongoDB's evolution from Master‑Slave to Replica Set and Sharding architectures, detailing how each model provides high availability, data reliability, and scalability, and offers practical configuration tips to ensure strong consistency and minimal downtime in production deployments.
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.
This article outlines the major new features of Redis 6.0 and 5.0, compares various deployment architectures—including master‑replica, cluster, and read‑write separation—explains proxy versus direct connection modes, and provides a Java Jedis connection‑pool code sample.
This article analyzes MySQL 8.0.25 source code, detailing the server‑layer architecture, parser reconstruction, query‑rewrite phases, transformation rules, and both the legacy and hypergraph optimizers, while also comparing key stages with PostgreSQL.
This article reviews Redis 6.0 and 5.0 new features, compares deployment architectures such as cluster, master-replica, and read-write split, and provides Java connection-pool code examples to help engineers select the appropriate Redis setup for performance, reliability, and scalability requirements.
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.
This article provides a comprehensive overview of InnoDB architecture, covering its memory structures, background threads, and key features like checkpoint mechanisms, double write, and neighbor page flushing, essential for understanding MySQL's default storage engine.
This article explains the background, architecture, and replication models of Redis read‑write separation, compares star and chain replication, and outlines its transparent compatibility, high availability, and performance benefits while noting consistency trade‑offs for read‑heavy workloads.
This article introduces the HR performance data preprocessing platform’s requirements, explains why HBase was selected as the storage solution, details its core concepts, architecture, data write/read processes, best practices, limitations, and presents performance metrics demonstrating its suitability for large‑scale, high‑throughput workloads.
This article explains how Redis read/write separation introduces a read‑only replica role, compares star and chain replication architectures, and outlines the transparent compatibility, high availability, and performance benefits that help users reduce costs while handling read‑heavy workloads.
This article explains how Redis read‑write separation works, compares star and chain replication architectures, and highlights the benefits of transparent compatibility, high availability, and high performance for read‑heavy, write‑light workloads.
This article explains the evolution of SQL Server high‑availability solutions, details the AlwaysOn availability‑group architecture, walks through its data‑synchronization workflow, compares synchronous and asynchronous commit modes, and offers practical guidance for deploying AlwaysOn in large‑scale enterprise environments.
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.
Tencent’s cloud‑native database TDSQL‑C separates compute and storage, offering petabyte‑scale network‑attached storage, automatic scaling, million‑level QPS, MySQL/PostgreSQL compatibility, serverless per‑use billing, two‑level caching, instant snapshot‑based backup and restore, and a roadmap toward ultra‑minimal operations, multi‑region DR and column‑store analytics.
The talk traces the evolution of distributed databases—from early shared‑memory and shared‑nothing designs through New‑SQL breakthroughs—to Tencent’s HTAP‑oriented TDSQL, highlighting its strong‑consistency architecture, anomaly taxonomy, and performance advantages over systems like Google Spanner while addressing modern scalability and hardware challenges.
Redis read/write separation introduces read‑only replicas to offload read traffic, offering two replication models—star replication with direct master‑replica sync and chain replication forming a replication chain—each with distinct performance, scalability, and latency trade‑offs, while maintaining high availability and transparent compatibility.
This article explains MySQL’s internal architecture—including server and storage engine layers—and walks through each stage of query processing from connection and authentication, through query cache, parsing, optimization, and execution, illustrated with a concrete SELECT example.
This article explains the HTAP concept, describes AnalyticDB PostgreSQL’s shift from a single‑master to a Multi‑Master design, details the architecture, distributed transaction handling, global deadlock detection, DDL support, fault tolerance, and presents benchmark results that demonstrate linear scalability for real‑time data‑warehouse workloads.
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.
This article reviews MySQL's evolution of high‑availability solutions—from classic master‑slave replication to InnoDB Cluster and InnoDB Replica Set—explaining each component, their features, deployment steps, and how to select the appropriate architecture based on business requirements such as RTO, RPO, and regional scope.
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.
This article explains the complete MySQL architecture, covering its connection, service, storage‑engine, and system‑file layers, the role of each component such as connection pools, query cache, parser, optimizer, executor, and the differences between InnoDB and MyISAM, providing practical insights for developers and interview preparation.
TiDB is a distributed NewSQL database that combines MySQL compatibility with a stateless SQL layer, a PD metadata manager, and a transactional key‑value store, offering automatic scaling, multi‑data‑center Raft replication, global secondary indexes, Percolator‑style 2PC, HTAP via TiFlash, and a rich ecosystem of migration, backup, CDC, and monitoring tools, as demonstrated by its large‑scale deployment at DeWu.
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.
This article compiles the most frequently asked MySQL‑related questions from developers and operations teams in banks, covering why MySQL is chosen over Oracle, compatibility gaps, migration methods, sharding strategies, performance tuning, consistency guarantees, and resource planning.
The fifth episode of the MySQL 冲冲冲 livestream explores the trade‑offs between sharding and middleware architectures, discusses distributed transaction challenges, compares DBLE with MyCat and other solutions, and provides practical guidance for developers and DBAs handling high‑throughput MySQL workloads.
The livestream discusses MySQL's high‑availability architectures compared with Oracle's, analyzes share‑nothing versus share‑everything designs, logical versus physical logging, and concludes that MySQL's share‑nothing and logical binlog replication are better suited for modern financial‑industry workloads, while also covering audience Q&A and upcoming topics.
This article provides a comprehensive overview of Apache HBase’s architecture, detailing its core components such as RegionServer, HMaster, ZooKeeper, WAL, MemStore, and HFiles, and explains key processes including read/write paths, compaction, region splitting, load balancing, and recovery mechanisms.
Three leading database experts from Tencent and cloud firms share how deep curiosity, hands‑on experimentation, persistent learning—combined with mastering distributed, cloud, and autonomous databases—forge an outstanding data craftsman, while advising newcomers to master performance, security, one DB per category, and start with open‑source tools.
This article outlines core database architecture principles—high availability, performance, scalability, and consistency—examines four common deployment patterns (primary‑standby, dual‑primary, primary‑replica with read/write separation, and hybrid), and presents practical consistency solutions and personal insights for selecting and evolving database designs.
This article breaks down MySQL’s architecture into its five key parts—connector, parser, optimizer, executor, and storage engine—explaining each component’s role from establishing connections and handling permissions to query parsing, execution planning, and data storage, with example commands and code snippets.
This article provides a comprehensive overview of Oracle Database Management System, covering its overall architecture, instance concepts, process structures, memory components, configuration schemes, program interfaces, data dictionary organization, and transaction handling mechanisms.
The article outlines vivo’s shift from traditional DBA firefighting to a product‑oriented database service model, detailing demand‑driven selection of MySQL, Redis, TiDB and others via a five‑dimensional radar, and the design of a unified, multi‑environment platform that emphasizes user experience, automation, and seamless cloud‑IDC integration.
This article explains MySQL's two‑layer architecture, the step‑by‑step execution flow of an SQL statement—including connection, query cache, parser, optimizer, executor, and storage engine—and the roles of redo log and binlog in ensuring data consistency.
This article provides a comprehensive technical overview of ClickHouse, covering its complete DBMS capabilities, column‑oriented storage and compression, vectorized execution engine, relational SQL support, diverse table engines, multi‑master clustering, sharding, and the design philosophies that make it exceptionally fast for large‑scale analytical workloads.
This article explains MySQL replication (master‑slave and master‑master), data sharding principles and implementations, and various distributed database deployment architectures, covering replication mechanisms, advantages, failure recovery, sharding strategies, middleware like Mycat, and scaling solutions for high‑availability systems.
This article explains why a fast‑growing e‑commerce platform chose MongoDB, covering its high‑availability replica‑set architecture, Raft‑based election algorithm, replica‑set size limits, write‑concern trade‑offs, sharding components and load‑balancing, as well as the flexible document schema with practical code examples.
MongoDB is a versatile NoSQL database that combines relational‑like querying with a flexible BSON document model, offering high performance, easy deployment, rich indexing, replication, and cloud‑scale storage, while supporting multiple programming languages and operating systems.
OceanBase, Alibaba’s self‑developed distributed relational database, achieved world‑leading TPC‑C performance in 2019 and shattered its own record in 2020, a journey marked by intense team effort, architectural innovations like Paxos‑based scalability, and a vision to become a global database leader.
This article details a real‑world implementation of Oracle GoldenGate for multi‑source data distribution, covering the architectural design, OGG fundamentals, operational challenges, troubleshooting steps, and future upgrade directions in a production environment.
This article provides a comprehensive analysis of Alibaba Cloud's AnalyticDB MySQL 3.0, detailing its cloud‑native architecture, storage and query innovations, the record‑breaking TPC‑DS benchmark results, and future directions for large‑scale, cost‑effective data warehousing.
This article explains Ctrip's high‑availability designs for SQL Server, MySQL, and Redis, describing multi‑replica strategies, evolution from legacy mirroring to AlwaysOn, multi‑node MHA management, and Redis sentinel‑based failover, while emphasizing fault‑tolerance across data centers.
The article analyzes HBase's CP‑oriented CAP limitations, proposes native AP support via Replica, decouples WAL IO to Kafka, optimizes MTTR, introduces multi‑datacenter active/active disaster recovery, and redesigns client write paths and LogSplit processing for higher availability and throughput.
This article objectively compares traditional sharding‑plus‑middleware architectures with modern NewSQL distributed databases, examining their design principles, distributed transaction handling, high‑availability mechanisms, scaling and sharding strategies, SQL support, storage engines, and overall maturity to help practitioners choose the most suitable solution for their workloads.
This article outlines core database architecture principles—high availability, high performance, consistency, and scalability—examines four common deployment schemes (primary‑standby, dual‑primary, primary‑replica with read/write separation, and a combined dual‑primary/replica model), and presents multiple consistency and cache‑integration solutions.
This article explains InnoDB's logical storage hierarchy of tablespaces, segments, extents, and pages, then details MySQL's partitioning concepts, types, creation syntax, and performance considerations, providing practical examples and guidance for effective database design.
This article explains the motivations for moving a high‑volume operation‑log system from MongoDB to Elasticsearch, outlines the existing architecture, details capacity planning, index design, and a step‑by‑step migration process using Kafka, DataX, and Spring Boot, and shares the performance gains and lessons learned.
This article outlines a comprehensive plan for deploying GaussDB T, covering the software architecture, component roles, and practical guidelines for single‑node, primary‑standby, and distributed setups, while highlighting common pitfalls and operational considerations for production environments.
This article outlines fundamental database architecture principles such as high availability, performance, consistency, and scalability, compares four common deployment schemes (master‑slave, dual‑master, master‑slave with read‑write separation, and hybrid master‑master‑slave), and presents various consistency solutions including caching, semi‑sync replication, and middleware.
This article explains Cassandra’s row‑oriented storage model, the multi‑step write and read processes, how tombstones and compaction manage data growth, and the impact of its distributed architecture on high availability, fault tolerance, and configurable consistency levels.
JDHBase, JD.com’s large‑scale KV store, powers billions of daily reads and writes across 7,000 nodes, and this article details its multi‑active, cross‑region architecture—including HBase replication fundamentals, Fox Manager routing, automatic failover policies, dynamic replication tuning, and serial replication to ensure strong consistency.
Distributed SQL databases combine the familiar relational SQL API with cloud‑native, horizontally scalable architectures, offering strong consistency, distributed ACID transactions, automatic sharding, fault‑tolerant replication, and low‑latency geo‑distribution, making them an agile, resilient choice for modern application development.
The article presents an in‑depth technical overview of Tencent Cloud's CynosDB, describing the challenges of traditional MySQL‑based cloud databases, detailing its compute‑storage decoupled architecture, redo‑log based replication, MVCC implementation, performance enhancements, and how these innovations address elasticity, stability, and resource utilization issues.
This article details the design principles, components, client implementation, data sharding, security mechanisms, high‑risk command blocking, configuration optimizations, and automated operational workflows of Qunar's Redis high‑availability cluster, including code modifications, deployment scripts, and platform‑based management for large‑scale production environments.
This article examines four common database architecture patterns—primary‑standby, dual‑primary, master‑slave read/write separation, and a hybrid dual‑primary + master‑slave—evaluating each against high availability, performance, consistency, and scalability, and then presents practical consistency‑resolution techniques and cache strategies.
The article examines whether MySQL, especially the Community Edition, faces commercial or regulatory “bottleneck” risks by reviewing US export control rules, Chinese policy guidance, and the technical feasibility of MySQL’s high‑availability architectures, concluding that current policies pose no significant threat.
This article outlines ClickHouse’s columnar OLAP architecture, dual‑center design, storage and write stability strategies, performance testing results, and practical query and system optimizations for handling petabyte‑scale data with high throughput and low latency requirements.
This article explains InfluxDB's retention policy components—duration, replication, and shard duration—clarifies the concepts of shards and shard groups, describes default configurations, offers recommendations for shard group duration, and outlines practical considerations for performance and data management.
This article explains MySQL’s fundamental concepts, distinguishing databases from instances, outlines the three‑layer MySQL architecture, and dives deep into InnoDB’s storage hierarchy—from tablespaces, pages, and row formats to .frm/.ibd files, record overflow handling, and the B+‑tree index structures that power fast queries.
This article introduces CB‑SQL, a MySQL‑compatible elastic database built on CockroachDB and RocksDB, explains RocksDB’s LSM‑tree design, details key configuration parameters, and describes the read/write/clear/file‑operation optimizations employed by CB‑SQL to achieve high scalability and stability.
This article explains the inner workings of relational databases, covering their architecture, indexing, time‑complexity analysis, query optimization, merge sort, client and query managers, caching strategies, transaction handling, ACID properties, concurrency control, and lock management.
This article provides a comprehensive introduction to Apache Kudu, covering its origins, cluster architecture with Raft consensus, table schema and partitioning design, and detailed storage mechanisms including MemRowSet, DiskRowSet, CFile, and compaction processes.
This article provides a comprehensive overview of InnoDB's file structure, covering physical organization from pages to tablespaces, logical structure including segments and indexes, and file management processes.
This article examines JD.com's massive HBase deployment, detailing its evolution from early adoption to a 90PB, 7,000‑node cluster, the platform's architecture, multi‑active disaster recovery, multi‑tenant isolation, and the integration of Phoenix for SQL‑based access, offering practical insights for large‑scale distributed storage.
This article outlines core database architecture principles—high availability, performance, consistency, and scalability—then compares four common setups (primary‑backup, dual‑master, primary‑replica, and hybrid), analyzes their trade‑offs, and presents practical consistency and cache‑sync solutions along with personal insights.
This article explains the concepts of unitization and multi‑active data centers, analyzes the drawbacks of single‑IDC deployments, and provides a detailed guide on implementing MySQL binlog synchronization while addressing common challenges such as data loops, duplicate inserts, unique‑index conflicts, and DDL handling, including practical solutions like GTID and auxiliary tables.
This article explains the importance of high availability in distributed systems, defines MySQL high‑availability concepts such as replication, describes several HA architectures including MySQL Cluster, MMM, and MHA, and discusses design principles for building resilient database services.
Fusion, Didi’s home‑grown C++ NoSQL database built on RocksDB, powers over 400 services and 1.5 PB of data, then evolved into the NewSQL layer dise with schema, secondary indexes, transactions and MySQL‑compatible binlog, and now guides a next‑gen distributed database project targeting true elastic scaling, distributed transactions and full SQL compatibility.
In this interview, Qunar.com’s database director Wang Zhufeng shares his six‑year journey, discusses the significance of the DTCC conference, outlines the evolution of Qunar’s MySQL architecture toward clustering, cloud‑native solutions, and data consistency, and offers advice for aspiring database engineers.
This article traces the historical laws that drove computing growth, examines how Redis, MongoDB and Memcached evolved, compares client‑side, proxy and compute‑storage‑separated architectures, evaluates their trade‑offs, and answers common questions about cloud‑based distributed databases.
This article examines core database architecture principles—high availability, performance, consistency, and scalability—and compares four common deployment patterns (primary‑standby, dual‑primary, primary‑replica with read/write separation, and a hybrid dual‑primary/replica design), followed by detailed consistency solutions and practical insights for real‑world implementation.
This article explains how JD.com leverages the open‑source HBase database for massive, low‑latency data storage across various business lines, detailing its architecture, multi‑tenant isolation, disaster‑recovery mechanisms, and integration with Phoenix SQL for OLTP workloads.
This article explains MySQL's internal architecture and the step‑by‑step execution flow of SELECT and UPDATE statements, covering server layers, storage engines, parsers, optimizers, executors, and the role of binlog and redo log in ensuring data consistency.
