MySQL vs MariaDB vs PostgreSQL: SQL Database Comparison

MySQL, MariaDB, and PostgreSQL are the leading open-source relational databases — MySQL offers widespread adoption and proven reliability, MariaDB provides MySQL compatibility with additional storage engines and performance improvements, and PostgreSQL delivers advanced features and standards compliance.

At a Glance

Key Differences

• Storage engines: MySQL uses InnoDB (transactional) and MyISAM (non-transactional). MariaDB extends this with Aria (MyISAM with crash recovery), XtraDB (InnoDB fork with better performance), and ColumnStore (columnar storage for analytics). PostgreSQL uses a single built-in storage engine with advanced features like BRIN indexes and custom access methods via extensions.
• JSON support: PostgreSQL has the best JSON support — JSONB stores data in binary format with full indexing (GIN indexes), enabling efficient querying of nested JSON documents. MySQL has a JSON data type with JSON path expressions. MariaDB offers both JSON and dynamic columns for schema-flexible storage.
• Advanced SQL features: PostgreSQL leads with common table expressions (CTE), window functions, recursive queries, table inheritance, foreign data wrappers, and partial/expression indexes. MySQL and MariaDB have improved their SQL feature set but still lag PostgreSQL in advanced analytics.
• Replication: MySQL offers Group Replication and InnoDB Cluster for high availability. MariaDB includes Galera Cluster (synchronous multi-master) built-in. PostgreSQL provides streaming replication (sync/async), logical replication for selective data distribution, and cascading replication.
• Licensing: MariaDB is fully open source under GPL. MySQL is also GPL but owned by Oracle — some features (e.g., enterprise monitoring, thread pool) are only in the commercial Enterprise Edition. PostgreSQL uses a liberal MIT-like license with no corporate ownership.

When to Choose MySQL

MySQL is the world’s most popular open-source database — it powers WordPress, Facebook, Twitter, and millions of web applications. MySQL with InnoDB provides excellent ACID compliance, foreign key support, and row-level locking. MySQL’s ecosystem is vast: tools like phpMyAdmin, Adminer, and Workbench; ORMs like Prisma, Sequelize, and Doctrine; and cloud services like Amazon RDS, Google Cloud SQL, and Azure Database. Choose MySQL for web applications, e-commerce platforms, and projects where you need the largest talent pool and most hosting options.

When to Choose MariaDB

MariaDB is the best choice for MySQL users who want additional performance and features without migration effort. MariaDB is a drop-in MySQL replacement — your existing applications, drivers, and tools work without changes. MariaDB’s XtraDB engine often outperforms InnoDB, and its optimizer improvements (subquery optimization, derived table merge) can accelerate complex queries. MariaDB’s Galera Cluster provides synchronous multi-master replication with automatic node failure handling. MariaDB’s ColumnStore engine is excellent for analytics workloads. Choose MariaDB when you want MySQL compatibility with better performance, more engines, and community-driven development.

When to Choose PostgreSQL

PostgreSQL is the best choice for complex data workloads — analytics, geospatial (PostGIS), time-series (TimescaleDB), and applications requiring advanced SQL features. PostgreSQL’s extension ecosystem is unmatched: PostGIS for geospatial, pgvector for vector similarity search (AI/ML), TimescaleDB for time-series, and Citus for distributed PostgreSQL. PostgreSQL’s MVCC architecture handles concurrent read/write workloads efficiently without read locks. Choose PostgreSQL for data-intensive applications, financial systems, geographic information systems, and AI/ML backends.

Architecture Comparison

    flowchart TD
    subgraph MySQL
        M1[Client] --> M2[SQL Optimizer]
        M2 --> M3{Storage Engine}
        M3 --> M4[InnoDB: ACID, transactions]
        M3 --> M5[MyISAM: non-transactional]
        M3 --> M6[Memory: in-memory]
    end
    subgraph MariaDB
        MA1[Client] --> MA2[SQL Optimizer]
        MA2 --> MA3{Storage Engine}
        MA3 --> MA4[InnoDB/XtraDB: ACID]
        MA3 --> MA5[Aria: crash-safe MyISAM]
        MA3 --> MA6[ColumnStore: analytics]
        MA3 --> MA7[Spider: sharding]
    end
    subgraph PostgreSQL
        P1[Client] --> P2[SQL Optimizer]
        P2 --> P3[Heap Storage]
        P3 --> P4[Indexes: B-tree, GiST, GIN, BRIN]
        P3 --> P5[Extensions: PostGIS, pgvector]
        P3 --> P6[Foreign Data Wrappers]
    end
  

Side by Side Code Example: Working with JSON Data

MySQL

CREATE TABLE events (
    id INT AUTO_INCREMENT PRIMARY KEY,
    data JSON
);

INSERT INTO events (data) VALUES
    ('{"user": "alice", "action": "login", "ip": "192.168.1.1"}'),
    ('{"user": "bob", "action": "purchase", "amount": 49.99}');

-- Query JSON fields
SELECT id, JSON_EXTRACT(data, '$.user') AS user,
       JSON_UNQUOTE(JSON_EXTRACT(data, '$.action')) AS action
FROM events
WHERE JSON_CONTAINS(data, '"login"', '$.action');

MariaDB

CREATE TABLE events (
    id INT AUTO_INCREMENT PRIMARY KEY,
    data JSON,
    -- Alternative: dynamic columns
    user VARCHAR(100) AS (JSON_VALUE(data, '$.user')) VIRTUAL
);

INSERT INTO events (data) VALUES
    ('{"user": "alice", "action": "login", "ip": "192.168.1.1"}'),
    ('{"user": "bob", "action": "purchase", "amount": 49.99}');

-- MariaDB supports JSON_VALUE for virtual columns
SELECT id, user, JSON_VALUE(data, '$.action') AS action
FROM events
WHERE JSON_EXISTS(data, '$.action');

PostgreSQL

CREATE TABLE events (
    id SERIAL PRIMARY KEY,
    data JSONB
);

INSERT INTO events (data) VALUES
    ('{"user": "alice", "action": "login", "ip": "192.168.1.1"}'),
    ('{"user": "bob", "action": "purchase", "amount": 49.99}');

-- GIN index for performant JSON queries
CREATE INDEX idx_events_data ON events USING GIN (data);

-- Query JSON fields with native operators
SELECT id, data->>'user' AS user,
       data->>'action' AS action
FROM events
WHERE data @> '{"action": "login"}';

All three databases store and query JSON data. MySQL uses JSON_EXTRACT() and JSON_CONTAINS() functions. MariaDB adds JSON_VALUE() for virtual computed columns. PostgreSQL uses native operators (->>, @>) with GIN indexes for fast JSON queries without full function calls.

FAQ