Postgres vs. MySQL

Relational databases have powered countless applications for decades, and they remain the backbone of many modern systems. When it comes to production-ready options there are two that stand out as the most widely used, PostgreSQL and MySQL. Both deliver solid performance, reliability, and community support, but there are notable differences in the way they handle data, their feature sets, and how easy they are to configure. Understanding these nuances can help you pick the right one for your specific needs.

TL;DR – When Should You Use PostgreSQL or MySQL?

The table below summarizes some of the biggest differences at a glance:

Feature Overview

PostgreSQL
PostgreSQL uses schemas to organize data within a single database, giving teams fine-grained control over permissions and logical data partitions. It also supports a wide range of data types, including JSON, arrays, ranges, and even custom-defined types, making it attractive for applications that handle complex or semi-structured data. The database uses Multi-Version Concurrency Control (MVCC) to reduce lock contention, so it typically excels at heavy write loads and complex queries that benefit from features like window functions and Common Table Expressions (CTEs). Another key strength is extensibility: you can add custom functions, operators, or extensions such as PostGIS for geospatial data—handy if your application requires specialized capabilities.

MySQL
MySQL, on the other hand, organizes data more simply, using distinct databases rather than schemas. This can make life easier for smaller projects or teams that want to keep data isolated by simply spinning up a new database. One of MySQL’s biggest selling points is its strong performance in read-heavy scenarios, especially when the InnoDB engine is paired with proper indexing and caching. It’s also known for straightforward replication, which many high-traffic websites use to distribute read operations across multiple servers and deliver faster responses to users around the globe. MySQL is generally easy to set up and has a vast knowledge base, which is appealing if you need to get a project off the ground quickly or if your team is already familiar with the MySQL ecosystem.

Database Details

Read/Write Throughput
MySQL typically shines in handling read-intensive workloads, provided that indexes and caching layers are properly tuned. Some large-scale users, such as Uber, have found success with MySQL even for hefty write loads, once the database is carefully configured. For straightforward inserts and updates, MySQL can match PostgreSQL in many benchmarks. However, PostgreSQL often takes the lead with more complex writes and intricate queries. Its concurrency features, enhanced by MVCC, reduce lock contention and allow it to maintain high performance in scenarios that involve numerous transactions simultaneously. With proper tuning, PostgreSQL can match or exceed MySQL’s performance in typical OLTP or analytical workloads.

Scalability
Both databases scale well, but they do so differently. PostgreSQL responds favorably to vertical scaling—adding more CPU, RAM, or faster storage often yields significant benefits. Horizontal scaling is a bit more involved; tools like PgBouncer for connection pooling and logical replication can help, and large platforms like Instagram and Notion have demonstrated that it can support vast user bases. MySQL has long been praised for its straightforward replication (master-replica), making it easy to offload read traffic and distribute those queries across multiple servers. This built-in replication setup is often enough for many use cases where global read scalability is paramount.

Indexing and Query Optimization
PostgreSQL provides diverse index types, such as B-tree, GiST, GIN, and BRIN, which cater to specific types of queries and can significantly enhance performance. It also has sophisticated JSON indexing and full-text search capabilities, though you may need to enable certain extensions. MySQL’s InnoDB engine primarily relies on B-tree indexes, suitable for most common query patterns, and it has some full-text indexing capability—though not as extensive as PostgreSQL’s.

Performance Tuning
Both PostgreSQL and MySQL require tuning parameters (e.g., buffer sizes, caching, checkpoint intervals) to optimize performance. PostgreSQL can be more involved, especially for new users, but with well-designed indexes and queries, either database can scale effectively in most production environments.

Recent Trends and Recognition
In recent years, PostgreSQL has been gaining popularity at a rapid pace, earning accolades like DBMS of the Year and making strides in developer surveys. Its permissive license and modern feature set continue to draw new users. Nonetheless, MySQL remains the most installed open-source relational database worldwide, fueled by Oracle’s backing and an enormous community. Its stability, simplicity, and ecosystem of hosting providers and tools ensure its continued dominance in many scenarios.

License Considerations
MySQL’s Community Edition is GPL licensed, which can be restrictive if you want to keep your own code proprietary. In that case, a commercial license from Oracle might be necessary. PostgreSQL’s license is similar to BSD/MIT, carrying fewer restrictions and no requirement to disclose your source code.

Technical Comparison
PostgreSQL’s object hierarchy is structured as Databases → Schemas → Tables, whereas MySQL uses Databases → Tables. PostgreSQL is fully ACID-compliant and can handle DML and DDL transactions; MySQL is also ACID-compliant through the InnoDB engine, and supports atomic DDL in version 8.0+. On the security front, PostgreSQL provides Row Level Security (RLS) out of the box, whereas MySQL requires workarounds such as views or stored procedures to mimic similar functionality.

In terms of replication, PostgreSQL supports both physical (WAL-based) and logical (pub/sub) methods. MySQL uses the binary log to facilitate logical replication and is commonly configured for read scaling with master-replica setups. JSON handling is more comprehensive in PostgreSQL, thanks to its robust indexing and array of functions. While MySQL also includes JSON features in version 8.0+, its indexing for JSON data is somewhat limited. PostgreSQL’s window functions and CTEs are more mature, although MySQL has caught up by adding these features recently. If you value extensibility, PostgreSQL offers a wide array of extensions—PostGIS for geospatial use cases, pg_stat_statements for detailed query insights, and the ability to define custom data types—while MySQL’s customization options focus on stored procedures and plugins.

Postgres vs MySQL Performance

In tests using Go clients with similar configurations:

1. Insert (Write) Test

   • Setup: Multiple virtual clients continuously insert randomized records.
   • Results:
     • PostgreSQL hovered around 19,000 inserts/second on a 4-CPU server with an SSD, versus MySQL’s 10,000.
     • PostgreSQL showed lower latency at the 99th percentile and used CPU, disk, and memory more efficiently.
     • MySQL performance dropped around 5,500 queries/second, incurring higher CPU usage.

2. Select (Read) Test

   • Setup: Queries involved a random event ID joined against a ~70-million-row customer table.
   • Results:
     • PostgreSQL again displayed lower latency, scaling nicely up to ~32,000 queries/second.
     • MySQL started showing latency spikes closer to 18,000 queries/second, tied to rising CPU usage.
     • Both eventually reached CPU saturation, but PostgreSQL stretched further before hitting a wall.

Key Takeaways

• Write Efficiency: PostgreSQL handled heavy insert loads with less resource usage.
• Read Performance: MySQL did well initially but dropped off sooner under high concurrency.
• Resource Utilization: PostgreSQL generally used fewer system resources at equivalent loads.

Real-world performance will vary depending on hardware, indexing strategy, query patterns, and configuration. Always test in an environment that reflects your production setup before making a final choice.

So, Postgres vs MySQL which is Better

• Consider PostgreSQL If

  • You need advanced features like window functions, CTEs, custom data types, or PostGIS for geospatial queries.
  • You expect complex or highly concurrent workloads.
  • You want a more permissive license with fewer restrictions.
  • You’re eager to tap into a rapidly expanding ecosystem and community.

• Consider MySQL If

  • Your primary focus is read-heavy workloads with straightforward queries.
  • You want something quick and simple to deploy, backed by a massive knowledge base.
  • Your team already knows MySQL, or your hosting environment is optimized for it.
  • You prefer easy replication for horizontal scaling.

The best approach is often to test both. Spin up a few instances, replicate your real-world workload, and see how each performs. You might discover one database naturally suits your data and query patterns better, especially once you factor in how comfortable your team is with each technology.

Conclusion

You might favor PostgreSQL if you need advanced features like window functions, CTEs, custom data types, or PostGIS for geospatial work. It also excels with heavier concurrency or complex workloads, and its permissive license won’t impose many restrictions on your own code. Meanwhile, MySQL remains a compelling choice if your application is read-heavy and you want something quick to deploy, especially if your team is already familiar with MySQL or your environment is optimized for it. Its simpler replication mechanisms are convenient for those who need to scale out reads.

In the end, the best approach is to test both databases in an environment that mirrors your production setup. Examine how they perform with your actual data, queries, and concurrency levels. The “better” option often comes down to factors like feature requirements, workload profiles, operational familiarity, licensing, and long-term scalability goals. While PostgreSQL’s feature set is attracting a fast-growing user base, MySQL’s proven track record and massive community ensure it will remain a mainstay for years to come.

Thanks for Reading! If you have any further suggestions or want to see additional metrics, don’t hesitate to reach out.