Databases (Core)
MongoDB vs PostgreSQL
Popular document database for flexible, JSON-like data models.
The world’s most advanced open-source relational database.
Side by side
- Pricing model
- MongoDBUsage-based
- PostgreSQLFlat rate
- Starting price
- MongoDB$9/mo (Atlas Flex)
- PostgreSQL$0
- Free tier
- MongoDBYes — Atlas free tier (512MB shared cluster)
- PostgreSQLYes — Free and open source
- Maturity
- MongoDB—
- PostgreSQLEstablished
- Availability
- MongoDBGenerally available
- PostgreSQLGenerally available
- Last checked
- MongoDBOct 12, 2026
- PostgreSQLOct 16, 2026
| Fact | MongoDB | PostgreSQL |
|---|---|---|
| Pricing model | Usage-based | Flat rate |
| Starting price | $9/mo (Atlas Flex) | $0 |
| Free tier | Yes — Atlas free tier (512MB shared cluster) | Yes — Free and open source |
| Maturity | — | Established |
| Availability | Generally available | Generally available |
| Last checked | Oct 12, 2026 | Oct 16, 2026 |
When each one fits
Choose MongoDB when…
Apps with flexible/evolving schemas
Document model avoids rigid migrations
Rapid prototyping with JSON data
Natural fit for JS/TS object shapes
MongoDB strengths
Flexible document model
Easy horizontal scaling
Atlas managed + vector search
Choose PostgreSQL when…
Most application databases
Reliable, flexible relational store with JSON support
RAG/AI apps via pgvector
Vector search alongside relational data
PostgreSQL strengths
Extremely capable and extensible
Rock-solid reliability
Ubiquitous managed options
Trade-offs
Known weaknesses from each tool’s record. Sourced ones link to where they came from.
MongoDB
Weaker for complex relational queries
No source on file
Atlas costs can grow
No source on file
PostgreSQL
Self-managing at scale is non-trivial
No source on file
Defaults need tuning for big workloads
No source on file