PostgreSQL vs MySQL: Compare Requirements, Versions, and Results

PostgreSQL and MySQL can both support transactional applications and analytical SQL. The useful comparison is between explicit versions, storage engines, required queries, and an operating plan. This guide compares PostgreSQL 16 core features with MySQL 8.4 using InnoDB; extensions, commercial editions, and managed services must be evaluated separately.

Start with the application contract

Write down the transactions that must be atomic, expected data size and growth, query shapes, concurrency, recovery objectives, and the skills of the team operating the system. An existing application dependency or supported hosting environment may outweigh an attractive feature. Company age, a popularity ranking, or an unverified claim that one engine is “faster” does not establish suitability.

Compare features at the correct scope

These are capability distinctions, not benchmark results. MySQL 8.4 supports recursive CTEs; treating it like an old 5.x release gives the wrong answer. PostgreSQL table partitioning does not automatically shard data across independent servers. A replica is not a backup against every operator error, and enabling replication does not itself implement safe automatic failover.

Concurrency: transactions can still wait and retry

Both engines use versioned data for important read paths, but that does not eliminate locks, deadlocks, or serialization failures. Test the actual multi-step transaction under the configured isolation level. A query that sees a stable result in one transaction mode may behave differently under another. Retrying an interrupted transaction also needs an application idempotency policy, especially when external side effects are involved.

Read the PostgreSQL isolation rules and InnoDB isolation rules before assuming equivalent behavior from shared SQL syntax. Keep reads and writes that must agree inside a deliberately designed transaction.

Use one small query as a portability check

This CTE, grouped aggregate, and dense rank use constructs supported by the compared versions. It was executed in PostgreSQL 16; MySQL support was checked against its documentation, not a native MySQL run. It is a correctness fixture, not a speed test:

WITH sales AS (
 SELECT 'A' AS region, 10 AS amount
 UNION ALL SELECT 'A',20
 UNION ALL SELECT 'B',30
), totals AS (
 SELECT region,SUM(amount) AS total FROM sales GROUP BY region
)
SELECT region,total,DENSE_RANK() OVER(ORDER BY total DESC) AS revenue_rank
FROM totals ORDER BY region;

region | total | revenue_rank
A | 30 | 1
B | 30 | 1

Next add the things that commonly break migrations: NULLs, tied ordering, identifier case, decimal division, text collation, timestamp conversion, generated keys, and duplicate-key handling. Compare exact results before latency. Benchmark with representative indexes, hardware, connection counts, warm and cold cache conditions, and write load. Record throughput and tail latency rather than announcing a universal winner from one SELECT.

Security is a configured property

PostgreSQL provides row security policies, but owners and privileged roles have important bypass behavior. Do not certify tenant isolation merely because a policy exists. Test with the real application role. For either engine, verify minimum privileges, authentication, encrypted connections, secret handling, backups, restore access, and update procedures in the selected deployment.

Encryption at rest, auditing, key management, firewalling, and failover can depend on the operating system, provider, extension, or product edition. A generic checkmark must not imply all of them are enabled in a core installation. Ask which component provides the feature and what failure test proves it works.

Extensions and JSON can decide the choice

If a required PostgreSQL extension supplies domain functionality, check its supported versions, upgrade path, hosting availability, and operational ownership. If a system already depends on MySQL-specific tooling or SQL semantics, migration has a real cost. Both engines support JSON, but storage, expression syntax, indexing, and validation are not interchangeable. A shared feature name is a prompt for a prototype, not proof of drop-in compatibility.

Evaluate the operating ecosystem

Make the team perform a backup and restore in a disposable environment, rotate a test credential, observe a slow query, and exercise a failover procedure if high availability is required. Confirm the drivers, monitoring tools, extension availability, and service limits actually supported by the chosen provider. Operator familiarity is useful evidence when recovery time matters.

Review licensing for the exact distribution

Use the official PostgreSQL license and MySQL legal policies for the exact server, connectors, and commercial products you plan to distribute or use. Do not infer every component’s terms from the engine’s name. Licensing decisions belong alongside deployment and distribution requirements.

Make a decision with evidence

Choose a short list based on mandatory requirements, then compare a representative transaction and two expensive reports. Reject candidates that cannot meet correctness, recovery, or operational constraints before optimizing a small latency difference. Retain the test queries, results, configuration, and reasons so the decision can be reviewed when the workload changes.

Recheck versions before the next upgrade

This comparison is version-scoped. A newer major release, extension, or managed service can change capabilities and defaults. Read release notes and rerun the same acceptance tests instead of carrying a feature matrix forward indefinitely. For date-type migration risks, see MySQL DATETIME versus TIMESTAMP.

Primary references

PostgreSQL CTEs, PostgreSQL JSON, materialized views, MySQL CTEs, and InnoDB document the compared features.