SQLite vs MySQL vs PostgreSQL

SQLite

SQLite is a lightweight, serverless, and self-contained database engine that stores all data in a single file on disk. Unlike MySQL and PostgreSQL, SQLite doesn’t require a separate server process, making it ideal for embedded systems (e.g. IoT), mobile apps, and small-scale applications. It supports standard SQL and is ACID-compliant but has limited concurrency capabilities because it locks the database during write operations. SQLite is best suited for applications with low-to-moderate read/write requirements and simpler data models.

MySQL

MySQL is a widely-used, server-based relational database optimized for high-performance read-heavy workloads. It’s a popular choice for web applications, content management systems, and e-commerce sites. MySQL offers various storage engines, with InnoDB being ACID-compliant and supporting transactions. It handles multiple concurrent connections efficiently and has made significant strides in supporting advanced features like full-text search and JSON data types. Its simple setup and high compatibility with web technologies make MySQL well-suited for dynamic websites and applications that prioritize speed and reliability.

PostgreSQL

PostgreSQL is an advanced, open-source relational database system known for its extensibility, high concurrency, and strong adherence to ACID principles. It supports a rich set of advanced features, including custom data types, full-text search, and JSONB for semi-structured data, making it highly versatile. PostgreSQL excels in complex, write-heavy applications and provides strong transactional integrity with features like Multi-Version Concurrency Control (MVCC). Ideal for enterprise and analytical applications, PostgreSQL handles complex queries and large-scale data processing with ease, offering robust support for applications requiring sophisticated data relationships and advanced querying capabilities.

1. Architecture and Setup

• SQLite:

  • Serverless and embedded, storing data in a single file on disk.
  • Requires no setup or configuration, simplifying deployment.
  • Ideal for mobile applications, small projects, and development environments.

• MySQL:

  • Server-based database system requiring installation and configuration.
  • Offers a traditional client-server architecture suitable for handling multiple concurrent connections.
  • Widely used in web applications and offers various storage engines (e.g., InnoDB and MyISAM).

• PostgreSQL:

  • Server-based, fully-featured database system with advanced capabilities.
  • Supports a client-server architecture and requires installation and configuration.
  • Known for its extensibility and support for advanced data types and functionalities.

2. Performance and Concurrency

• SQLite:

  • Best for lightweight, single-user applications and read-heavy workloads.
  • Has limited concurrency capabilities because it locks the database during write operations.
  • Supports Write-Ahead Logging (WAL) mode to improve concurrency.

• MySQL:

  • Optimized for read-heavy operations with high concurrency.
  • Handles read/write operations efficiently, with improvements in write performance in recent versions.
  • Supports replication and sharding, allowing for scaling read-heavy workloads.

• PostgreSQL:

  • Excels in handling complex queries, transactional integrity, and write-heavy operations.
  • Uses Multi-Version Concurrency Control (MVCC) to handle high concurrency without locking issues.
  • Ideal for applications requiring complex data relationships and frequent writes.

3. Data Integrity and ACID Compliance

• SQLite:

  • Fully ACID-compliant but may struggle with complex transactional workflows due to locking mechanisms.
  • Suitable for applications with simple transactional requirements.

• MySQL:

  • Offers ACID compliance primarily when using the InnoDB storage engine.
  • Suitable for applications requiring reliable transactional integrity, such as e-commerce or content management systems.

• PostgreSQL:

  • Fully ACID-compliant with advanced transaction features like nested transactions and savepoints.
  • Known for robust data integrity, making it ideal for financial applications, data warehousing, and enterprise-level applications.

4. Features and Extensibility

• SQLite:

  • Supports standard SQL commands, views, and triggers.
  • Lacks support for stored procedures and some advanced functionalities.
  • Not suitable for complex data structures or advanced analytical functions.

• MySQL:

  • Supports standard SQL and common database features like triggers, stored procedures, and indexing.
  • Offers full-text search capabilities and JSON data types since version 5.7.
  • Less extensible compared to PostgreSQL but widely compatible with various web technologies.

• PostgreSQL:

  • Highly extensible with support for custom functions, data types, and operators.
  • Offers advanced features like full-text search, JSONB, geospatial data (PostGIS), timeseries data (TimescaleDB), and recursive queries.
  • Supports complex data types and analytical functions, making it highly flexible for various applications.

5. Use Cases

• SQLite:

  • Ideal for small projects, mobile applications, and embedded systems.
  • Commonly used in development environments or as a lightweight data store.

• MySQL:

  • Popular for web applications, e-commerce platforms, and content management systems (e.g., WordPress).
  • Well-suited for applications requiring fast transactions and read-heavy workloads.

• PostgreSQL:

  • Preferred for complex applications that require strong data integrity and advanced querying capabilities.
  • Suitable for analytics, financial applications, enterprise databases, and applications needing complex data relationships.

6. Community and Ecosystem

• SQLite:

  • Large community with ample documentation and support.
  • Widely used in smaller applications and mobile development, ensuring compatibility with many libraries and tools.

• MySQL:

  • Very large and active community with extensive resources and support.
  • Supported by major cloud providers (e.g., AWS RDS, Azure Database), facilitating cloud deployments.
  • Forks like MariaDB offer additional features and flexibility.

• PostgreSQL:

  • Strong, active community focused on innovation and stability.
  • Widely supported by tools and libraries, with a rich ecosystem for advanced features like PostGIS and TimescaleDB.
  • Supported by major cloud providers, making it suitable for scalable cloud deployments.