PostgreSQL vs MySQL for Industrial Web Applications: A Practical Comparison

MySQL: Simple, Fast, Universally Supported

MySQL is the default choice for web applications globally and for good reason — it is simple to operate, well-documented, and supported by every hosting provider and cloud platform. For straightforward CRUD operations (ERP transactions, production records, user management), MySQL is excellent. The ecosystem is mature: Sequelize, TypeORM, and Knex.js all support MySQL seamlessly.

PostgreSQL: More Powerful, More Complex

PostgreSQL has features MySQL lacks: native JSON/JSONB columns (useful for flexible machine configuration data), full-text search, array data types, table inheritance, and a more sophisticated query planner. For analytical queries common in industrial dashboards — complex JOINs across large time-series tables — PostgreSQL typically outperforms MySQL by 20–50%.

TimescaleDB: PostgreSQL for Time-Series

TimescaleDB is a PostgreSQL extension that makes it dramatically more efficient for time-series data (machine measurements, sensor readings). time_bucket() for aggregation, automatic data retention policies, and compression reduce storage by 90% compared to standard PostgreSQL for time-series workloads. If your application has significant machine data, use TimescaleDB.

Our Recommendation by Use Case

Use MySQL for: ERP and MES relational data, user authentication, order management, inventory. Use PostgreSQL for: analytical queries, complex reporting, applications using JSONB for flexible schemas. Use TimescaleDB (PostgreSQL extension) for: all time-series machine data, sensor readings, OEE history. Many of our systems use MySQL and TimescaleDB together — relational data in MySQL, time-series in TimescaleDB.