If you’re a MySQL developer looking to expand your database skills, PostgreSQL is a natural next step. While both are powerful relational database management systems (RDBMS), PostgreSQL offers advanced features that can take your database expertise to the next level. In this guide, I’ll help you leverage your MySQL knowledge to quickly get up to speed with PostgreSQL.

Understanding the Key Differences

Before diving in, it’s important to understand the fundamental differences between MySQL and PostgreSQL. While they share many similarities as SQL databases, their philosophies differ significantly.

MySQL has traditionally focused on speed and simplicity, making it a popular choice for web applications. PostgreSQL, on the other hand, emphasizes standards compliance, data integrity, and advanced features. This difference in approach leads to several practical distinctions you’ll need to know.

Syntax Differences That Matter

One of the first things you’ll notice when switching from MySQL to PostgreSQL is the syntax variations. While much of standard SQL remains the same, there are some important differences.

In MySQL, you might use LIMIT with an OFFSET like this:

SELECT * FROM users LIMIT 10 OFFSET 20;

PostgreSQL supports this syntax, but also offers the more standard:

SELECT * FROM users OFFSET 20 LIMIT 10;

Another key difference is string concatenation. MySQL uses CONCAT() or the || operator (in ANSI mode), while PostgreSQL always uses || for string concatenation:

— MySQL
SELECT CONCAT(first_name, ‘ ‘, last_name) FROM users;

— PostgreSQL
SELECT first_name || ‘ ‘ || last_name FROM users;

Auto-increment columns also work differently. MySQL uses AUTO_INCREMENT:

CREATE TABLE users (
id INT AUTO_INCREMENT PRIMARY KEY,
username VARCHAR(50)
);

PostgreSQL uses SERIAL or IDENTITY:

CREATE TABLE users (
id SERIAL PRIMARY KEY,
username VARCHAR(50)
);

— Or in PostgreSQL 10+
CREATE TABLE users (
id INT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
username VARCHAR(50)
);

Data Types: More Than Meets the Eye

PostgreSQL’s type system is significantly more robust than MySQL’s. While MySQL has basic types that work well for most applications, PostgreSQL offers specialized types that can make your database more efficient and expressive.

For example, PostgreSQL has native support for arrays:

CREATE TABLE articles (
id SERIAL PRIMARY KEY,
title VARCHAR(200),
tags TEXT[]
);

INSERT INTO articles (title, tags)
VALUES (‘Learning PostgreSQL’, ARRAY[‘database’, ‘postgresql’, ‘tutorial’]);

PostgreSQL also includes JSON and JSONB types for storing and querying JSON data efficiently. JSONB (binary JSON) is particularly powerful because it supports indexing:

CREATE TABLE products (
id SERIAL PRIMARY KEY,
name VARCHAR(100),
attributes JSONB
);

CREATE INDEX idx_attributes ON products USING GIN (attributes);

SELECT * FROM products WHERE attributes @> ‘{“color”: “blue”}’;

Other PostgreSQL-specific types include UUID, INET (for IP addresses), and geometric types—none of which have direct equivalents in MySQL.

Transaction and Concurrency Control

Both MySQL (with InnoDB) and PostgreSQL support ACID transactions, but PostgreSQL’s implementation offers some advantages.

PostgreSQL uses Multi-Version Concurrency Control (MVCC) consistently across all isolation levels. This means readers never block writers and writers never block readers, leading to better concurrent performance in many scenarios.

The transaction isolation levels also behave differently. PostgreSQL’s default isolation level is READ COMMITTED, which provides better protection against certain anomalies than MySQL’s default REPEATABLE READ.

You can set the isolation level in PostgreSQL like this:

BEGIN TRANSACTION ISOLATION LEVEL SERIALIZABLE;
— Your queries here
COMMIT;

Advanced Features You’ll Love

Once you’re comfortable with the basics, PostgreSQL’s advanced features will really start to shine.

Common Table Expressions (CTEs) and recursive queries are fully supported:

WITH RECURSIVE subordinates AS (
SELECT employee_id, manager_id, name
FROM employees
WHERE employee_id = 1
UNION ALL
SELECT e.employee_id, e.manager_id, e.name
FROM employees e
INNER JOIN subordinates s ON s.employee_id = e.manager_id
)
SELECT * FROM subordinates;

Window functions provide powerful analytical capabilities:

SELECT
name,
department,
salary,
AVG(salary) OVER (PARTITION BY department) as dept_avg_salary,
RANK() OVER (PARTITION BY department ORDER BY salary DESC) as dept_rank
FROM employees;

Full-text search is built into PostgreSQL with the tsvector and tsquery types:

SELECT title, ts_rank(to_tsvector(content), query) AS rank
FROM articles, to_tsquery(‘postgresql & database’) query
WHERE to_tsvector(content) @@ query
ORDER BY rank DESC;

Practical Tips for MySQL Developers

Here are some practical tips to help smooth your transition:

1. Case Sensitivity: PostgreSQL treats unquoted identifiers as lowercase, while MySQL’s behavior depends on the operating system. Always use lowercase for table and column names, or quote them with double quotes if you need mixed case.
2. Boolean Values: PostgreSQL has a true BOOLEAN type. Use TRUE/FALSE instead of 1/0.
3. String Comparison: PostgreSQL is strict about type matching. You can’t directly compare strings to integers without explicit casting.
4. EXPLAIN Plans: Both databases have EXPLAIN, but PostgreSQL’s output is more detailed. Use EXPLAIN ANALYZE to get actual execution statistics.
5. Database vs. Schema: In MySQL, database and schema are synonyms. In PostgreSQL, a database contains schemas, and schemas contain tables. The default schema is ‘public’.

Development Workflow Differences

Your development workflow will also need some adjustments. PostgreSQL uses different tools and conventions:

• Instead of phpMyAdmin, you’ll likely use pgAdmin or DBeaver for GUI management
• The command-line tool is psql instead of mysql
• Configuration is in postgresql.conf and pg_hba.conf rather than my.cnf
• User authentication and permissions work differently—PostgreSQL has more granular control

Performance Tuning Considerations

Performance tuning in PostgreSQL requires understanding some key differences:

VACUUM is crucial in PostgreSQL due to MVCC. Deleted or updated rows aren’t immediately removed, so regular VACUUM operations are necessary:

VACUUM ANALYZE table_name;

Indexing strategies differ too. PostgreSQL supports multiple index types (B-tree, Hash, GiST, GIN, BRIN) beyond MySQL’s B-tree and hash indexes. Choosing the right index type can dramatically improve performance.

The query planner also works differently. PostgreSQL maintains detailed statistics about your data and uses a sophisticated cost-based optimizer. Running ANALYZE regularly helps the planner make better decisions.

Getting Hands-On Experience

The best way to learn PostgreSQL is to actually use it. Here’s a suggested learning path:

1. Install PostgreSQL locally and set up a test database
2. Convert one of your MySQL projects to PostgreSQL
3. Experiment with PostgreSQL-specific features like arrays and JSONB
4. Build a small project that leverages advanced features like window functions or full-text search
5. Read the official PostgreSQL documentation—it’s excellent and comprehensive

Conclusion

Transitioning from MySQL to PostgreSQL isn’t as daunting as it might seem. Your SQL knowledge transfers well, and the differences are mostly about learning new syntax and understanding PostgreSQL’s richer feature set.

The effort is worth it. PostgreSQL’s advanced features, strong standards compliance, and excellent documentation make it a powerful tool for any database developer. Whether you’re building complex analytical systems, handling geospatial data, or just want a more robust database platform, PostgreSQL has you covered.

Start with the basics, experiment with the advanced features, and before long you’ll wonder how you ever lived without PostgreSQL’s capabilities. The journey from MySQL to PostgreSQL isn’t just about learning a new database—it’s about expanding what’s possible with your data.