PostgreSQL和MySQL的全面比较

介绍

让我们快速了解一下 PostgreSQL 和 MySQL。这两者都是重要的开源关系数据库管理系统，广泛应用于不同的应用程序。

技术架构和设计理念

起源与发展

PostgreSQL起源于1986年伯克利的POSTGRES项目，旨在通过严谨的学术研究和严格的SQL标准来推进数据库管理系统。这一背景为 PostgreSQL 提供了专注于数据一致性的坚实理论基础，使其成为复杂查询和高级数据类型的理想选择。其设计强调长期稳定性、可扩展性和社区驱动的创新。

相比之下，MySQL 由 Michael Widenius 和 David Axmark 创建于 1995 年，优先考虑实用性和易用性，以满足快速发展的互联网应用的需求。它简化了数据库管理并提高了性能，在互联网繁荣时期迅速成为 Web 开发人员的首选。 MySQL 的重点始终是性能和易于部署。

数据库引擎

MySQL 的显着特点是支持多种数据库引擎，允许用户根据自己的需求选择最佳的存储方式。从5.5版本开始，InnoDB一直是默认引擎，支持事务和行级锁定，以实现高并发和数据一致性。 MyISAM虽然提供了更好的读性能，但缺乏事务支持，适合读密集型场景。 MySQL 还为特定用例提供了 Memory 和 Archive 等引擎。

相比之下，PostgreSQL 使用统一的核心引擎，确保所有功能的一致性和互操作性。此设计支持复杂查询、事务管理和高级数据类型，同时简化维护。尽管在某些情况下不如 MySQL 灵活，但 PostgreSQL 的内部灵活性和可扩展性通过分区和查询优化等功能得到了增强。

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比较 SQL 语法和功能

比较分析揭示了数组类型支持、JSON 处理、事务管理、临时表、窗口函数、递归查询、数据类型丰富性、默认值约束和区分大小写等方面的差异和相似之处：

Array TypesSupportedNot directly supportedPostgreSQL allows direct definition of array type fields. MySQL simulates arrays using strings or other indirect methods.JSON SupportPowerfulMore basicPostgreSQL has advanced JSON support with indexing and optimized queries. MySQL’s JSON support has improved in recent versions but remains simpler.Transaction HandlingFully ACIDDefault auto-commitPostgreSQL pulls off full ACID compliance by default, ideal for high-consistency scenarios. MySQL defaults to auto-commit for each statement but can be configured for transaction handling.Temporary TablesSession/Global ScopeSession OnlyPostgreSQL allows both session-level and global temporary tables, while MySQL supports only session-level ones.Window FunctionsSupportedSupported since later versionsPostgreSQL has long supported window functions; MySQL added full support in more recent versions.CTE (Common Table Expressions)SupportedSupportedBoth support CTE, but advanced usages or performance may vary.Recursive QueriesSupportedSupported since version 8.0PostgreSQL has supported recursive queries for a while, while MySQL started in version 8.0.Data TypesMore varied (like ARRAY, HSTORE, GIS types)Basic types are comprehensivePostgreSQL supports more specialized data types, while MySQL has a good set of basic types but not as diverse as PostgreSQL.Default Value ConstraintsSupports any expressionHas many limitationsPostgreSQL allows defaults to be any expression, whereas MySQL’s defaults are usually constants.Case SensitivityConfigurableDefaults to case-insensitivePostgreSQL can configure case sensitivity at the database or column level, while MySQL defaults to case-insensitive unless using binary collation.

注意：随着时间的推移，两个系统都会不断更新，特定功能的支持和性能可能会发生变化。选择数据库时最好查阅最新的官方文档或发行说明。

高级功能比较：数据类型和事务处理

Advanced Data TypesSupports arrays, JSONB, hstore, etc., for complex data structures.Supports JSON (enhanced in newer versions), but doesn’t natively support arrays or hstore, needing indirect methods.Window FunctionsEarly support for window functions, suitable for a variety of complex data analytics scenarios.Added window functions in newer versions, progressively improving functionality but might lag in maturity and community resources.Transaction Isolation LevelsSupports READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, SERIALIZABLE, fully compliant with SQL standards.Also supports these four isolation levels, but defaults to REPEATABLE READ and implements them via different storage engines (like InnoDB).MVCC ImplementationStrong MVCC mechanism maintains multiple versions for each row, allowing for lock-free reads to enhance concurrency.InnoDB uses MVCC via Undo Logs to maintain transaction views, optimizing read and write concurrency with its own locking strategies.Locking MechanismSupports row-level locking combined with multi-version concurrency control, reducing lock contention and improving concurrency efficiency.InnoDB supports row-level locking; MyISAM and other engines use table locks. Row-level locking improves concurrency but can be influenced by locking strategies and transaction designs.

数据类型和功能特征

高级数据类型：PostgreSQL 提供了更丰富的选项，如数组、JSONB、hstore，使其适合复杂的数据处理。窗口函数和分析查询：PostgreSQL 早期已经支持这些，而 MySQL 在较新的版本中添加了它们。事务处理和并发控制：比较它们的隔离级别、MVCC 实现和锁定机制，显示出关键差异。

性能和可扩展性比较

Benchmarking and Workload- Excels in complex queries and joins, thanks to rich indexing types and an optimizer.
– Good balance for write-heavy and mixed workloads.- Performs excellently in read-heavy scenarios, especially simple SELECT queries.
– InnoDB engine optimizes read speed and handles concurrency well.Scalability Strategy- Supports partitioning for large tables to optimize query performance.
– Parallel querying enhances large data processing capabilities.
– Connection pooling management boosts concurrent processing.- Achieves scalability via third-party tools (like PgPool-II, Patroni) for high availability and extensibility.
– Sharding is common for horizontally scaling, ideal for large data distribution.
– Offers replication (master-slave), group replication for redundancy and separating reads and writes.Horizontal Scalability- Native support is limited but can implement complex distributed deployments with third-party tools.
– Citus extension enables real distributed SQL processing.- Has more mature sharding solutions and clustering technologies, making horizontal scalability more flexible, especially for large internet applications.

性能和可扩展性的深入比较

Benchmarking and Workload- With a powerful query optimizer and various indexing types, excels in complex query handling and analysis.
– Balanced reading and writing, suitable for applications needing high-performance writing and complex analysis.
– Excels in read-heavy contexts, particularly in simple SELECT queries, suited for web browsing and content distribution scenarios.
– Optimizes read performance through read-write separation and caching strategies.- Specializes in read-heavy operations for simple SELECT queries, perfect for content management systems and e-commerce platforms, ensuring optimized reading performance.
– MySQL supports InnoDB optimizations for read speed and concurrency handling.Scalability Solutions- Partitions support range, list, hash, and more, boosting large table query efficiency.
– Automatically leverages multi-core CPUs for parallel querying, enhancing data retrieval speed.
– 内置和第三方连接池管理优化资源使用和响应时间。
– Using extensions like Citus for distributed processing.
– Sharding, either manual or automated, disperses storage and processes large datasets to improve read and write performance.
– Replication mechanisms (master-slave, group) enhance data availability and reading scalability.- InnoDB Cluster provides integrated high availability and scalability solutions that simplify cluster management.

性能和可扩展性

基准测试和工作负载：分析两个系统在不同工作负载下的性能，提到 MySQL 在读取密集型环境中的优势以及 PostgreSQL 在复杂查询中的效率。可扩展性：讨论它们的水平可扩展性能力：MySQL 的分片策略与 PostgreSQL 的连接池、分区和并行查询功能。

安全性和合规性比较

User Permission Management- Fine-grained permission control with role and privilege inheritance, making it easier to manage complex permission structures.
– Supports row-level security (RLS) for custom access control rules.
– Provides a detailed user and permissions management system, with controls down to the database and table level.- Doesn’t natively support row-level security but can implement it through application logic.Encryption Features- Supports SSL/TLS encrypted connections to secure data transmission.
– Has field-level encryption plugins to enhance security when data is at rest.
– Transparent Data Encryption (TDE) options can be implemented through third-party extensions.- Built-in SSL/TLS support protects network communications.
– InnoDB storage engine supports table space encryption to secure data files.
– MySQL Enterprise Edition offers more advanced encryption options.Compliance Certification- Complies with multiple security standards, including FIPS 140-2 and Common Criteria.
– Supports data protection regulations like GDPR, but specific compliance measures need to be tailored to the environment.- Holds several international security certifications like PCI DSS and ISO 27001.
– Supports SSL/TLS and TDE, aiding in compliance with regulations like HIPAA and GDPR.
– MySQL Enterprise Edition provides enhanced auditing and security functions to strengthen compliance.

安全与合规性

用户权限管理：PostgreSQL 擅长细粒度控制和行级安全性。 MySQL专注于应用层安全适配。加密功能：两者都支持 SSL/TLS，但 PostgreSQL 通过扩展和对字段级加密的高级控制来包含 TDE 选项。合规认证：两个数据库都遵守各种安全标准，但PostgreSQL拥有更广泛的认可认证，而MySQL的企业版则增强了合规能力。

应用场景及选型建议

PostgreSQL- Data analytics and business intelligence: Strong capabilities for complex queries, window functions, and geospatial data processing.
– High compliance industries like finance and healthcare: Robust security and compliance features.
– Complex application development: Supports advanced data types and multi-version concurrency, ideal for transaction-heavy applications.MySQL- Web applications and startups: Lightweight, easy to deploy, rich community resources, quick development cycles.
– Read-heavy services: Such as content management systems and e-commerce platforms with optimized read performance.
– Cloud-native environments: Deep integration with various cloud providers, suited for quickly scalable internet services.

决策框架

Data Scale and ComplexityVolume of data, query complexityLarge datasets, complex queries, multi-dimensional analysisSmall to medium datasets, simple queriesTransaction Processing NeedsComplexity and consistency of transactionsHigh-concurrency transactions, strict ACID requirementsSimple transaction handling, read/write separation scenariosBudget and CostsSoftware licensing, operational costsOpen-source and free, but may require more professional supportOpen-source and low cloud service costsTeam Familiarity and SkillsTechnical stack match, learning curveRequires strong SQL skills, suited for experienced teamsFriendlier for beginners, lower learning curve

注意事项

选择数据库时，没有一刀切的选择。相反，专注于最适合您需求的内容。在权衡这些因素时，请考虑运行小规模概念验证 (POC)，以测试特定工作负载下的数据库性能，然后再做出最终决定。此外，这两个数据库系统都在不断改进并引入新功能，因此了解最新发展对于做出明智的选择至关重要。

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