MySQL vs PostgreSQL: Which Database in 2026?

Head-to-Head Comparison

Here's a quick overview of how PostgreSQL and MySQL stack up across the most important decision criteria:

Performance & Scores

Based on real-world usage, community feedback, and benchmark data, here's how each scores across key dimensions (out of 100):

JSON Storage: PostgreSQL's Decisive Advantage

For modern web applications that need to store semi-structured data, PostgreSQL's JSONB type is a significant advantage. JSONB is stored in a binary format that supports full indexing:

-- PostgreSQL JSONB with index
CREATE TABLE products (
  id SERIAL PRIMARY KEY,
  metadata JSONB
);

CREATE INDEX ON products USING GIN (metadata);

-- Query JSON fields efficiently
SELECT * FROM products 
WHERE metadata @> '{"category": "electronics"}';

-- Update nested JSON
UPDATE products 
SET metadata = metadata || '{"featured": true}'
WHERE id = 42;

MySQL's JSON support has improved in version 8.0 but still lacks the indexing flexibility and operator richness of PostgreSQL's JSONB.

pgvector: PostgreSQL for AI Applications

One of the most important developments in 2023-2024 is pgvector, a PostgreSQL extension that adds vector similarity search. This is what enables semantic search, recommendation systems, and RAG (Retrieval-Augmented Generation) patterns for AI applications.

-- Install pgvector extension
CREATE EXTENSION vector;

-- Store embeddings
CREATE TABLE documents (
  id SERIAL PRIMARY KEY,
  content TEXT,
  embedding vector(1536)  -- OpenAI ada-002 dimensions
);

-- Nearest-neighbor search
SELECT content, embedding <-> $1 AS distance
FROM documents
ORDER BY distance
LIMIT 5;

MySQL has no equivalent. If you're building any AI-powered features, PostgreSQL + pgvector is a strong reason to choose it.

When to Use Which

Related Comparisons