MongoDB for flexible schemas and horizontal scaling, PostgreSQL for relational data, transactions, and referential integrity. This choice is one of the most common architectural decisions, and the right answer depends on the specific workload. In recent years, the boundary has blurred — MongoDB added transactions, PostgreSQL improved JSONB. Yet they have fundamentally different strengths.
MongoDB¶
- Flexible schema — schema-less design, each document can have a different structure
- Horizontal scaling — native sharding distributes data across clusters
- Aggregation pipeline — powerful framework for analytical queries over documents
- Document model — JSON-like BSON format, natural for modern applications
MongoDB excels when the schema changes frequently, data is hierarchical (nested objects, arrays), and you need horizontal scaling. Sharding automatically distributes data by shard key, replica sets ensure high availability.
PostgreSQL¶
- ACID transactions — strong consistency guarantees, ideal for financial data
- Relational model — referential integrity, foreign keys, constraints
- JSONB — semi-structured data in a relational DB with GIN indexes for fast queries
- Mature ecosystem — extensions (PostGIS, pg_vector, TimescaleDB), replication, partitioning
PostgreSQL with JSONB offers the best of both worlds — the relational model for structured data and JSONB columns for flexible parts. GIN indexes on JSONB enable fast document queries without compromising relational data.
When to Use Which¶
- MongoDB — CMS, product catalogs, rapid prototyping, event sourcing, frequently evolving schema
- PostgreSQL — financial transactions, e-commerce, reporting, relational data with referential integrity
- PostgreSQL with JSONB — hybrid workload, often replaces the need for MongoDB
PostgreSQL for Most Cases¶
PostgreSQL with JSONB covers most use cases. Choose MongoDB for specific document workloads with native sharding and high-volume writes distributed across regions.