MongoDB
Document-oriented NoSQL database
Postgres
The world's most advanced open-source relational DB
MongoDB is a document database — flexible schemas, built-in sharding, great for unstructured data and rapid prototyping. Postgres is relational but its JSONB type covers most 'flexible schema' use-cases while also giving you joins, transactions, and stricter integrity.
Pick MongoDB when documents map naturally to your domain and you want built-in horizontal sharding.
Pick Postgres when you need joins, strong consistency, or mix structured and JSON data in one DB.
| Feature | 🍃MongoDB | 🐘Postgres | Winner |
|---|---|---|---|
| Data model | BSON documents | Relational + JSONB | Tie |
| Schema enforcement | Optional (JSON Schema) | Strict by default | B |
| Transactions | Multi-doc since 4.0 | ACID from day one | B |
| Horizontal scaling | Built-in sharding | External (Citus) | A |
| Joins / aggregations | Aggregation pipeline | Full SQL joins | B |
| Vector search | Atlas Vector Search | pgvector extension | Tie |
| Write scalability | Excellent | Good | A |
| Ecosystem maturity | Strong | Stronger (decades) | B |
Data model
TieMongoDB
BSON documents
Postgres
Relational + JSONB
Schema enforcement
BMongoDB
Optional (JSON Schema)
Postgres
Strict by default
Transactions
BMongoDB
Multi-doc since 4.0
Postgres
ACID from day one
Horizontal scaling
AMongoDB
Built-in sharding
Postgres
External (Citus)
Joins / aggregations
BMongoDB
Aggregation pipeline
Postgres
Full SQL joins
Vector search
TieMongoDB
Atlas Vector Search
Postgres
pgvector extension
Write scalability
AMongoDB
Excellent
Postgres
Good
Ecosystem maturity
BMongoDB
Strong
Postgres
Stronger (decades)
Best for
Best for
MongoDB→Postgres means schema design: flatten nested docs, decide which sub-documents become JSONB vs separate tables, rewrite aggregation pipelines as SQL CTEs. Tools: mongodb-to-sql or a Node.js ETL with @supabase/supabase-js. Postgres→MongoDB: denormalize joins into nested documents, reimplement FK constraints at app layer.
MongoDB is a document database — flexible schemas, built-in sharding, great for unstructured data and rapid prototyping. Postgres is relational but its JSONB type covers most 'flexible schema' use-cases while also giving you joins, transactions, and stricter integrity. In short: MongoDB — Document-oriented NoSQL database. Postgres — The world's most advanced open-source relational DB.
Pick MongoDB when documents map naturally to your domain and you want built-in horizontal sharding.
Pick Postgres when you need joins, strong consistency, or mix structured and JSON data in one DB.
MongoDB→Postgres means schema design: flatten nested docs, decide which sub-documents become JSONB vs separate tables, rewrite aggregation pipelines as SQL CTEs. Tools: mongodb-to-sql or a Node.js ETL with @supabase/supabase-js. Postgres→MongoDB: denormalize joins into nested documents, reimplement FK constraints at app layer.
Yes. Both have MCP servers installable via MCPizy (mcpizy install mongodb and mcpizy install postgres). They work identically across Claude Code, Claude Desktop, Cursor, Windsurf, and any other MCP-compatible client. You can install both side by side and route queries in your agent's prompt.
Supabase is managed Postgres plus auth, storage, edge functions, and realtime. Plain Postgres gives you the same battle-tested engine without the batteries — you run it yourself. Supabase wins for speed-to-product; Postgres wins for full control and cost at scale.
Both are BaaS offerings. Supabase is Postgres-based (relational, SQL, open-source), Firebase is Firestore-based (NoSQL, proprietary, Google Cloud). Supabase wins if you want SQL, lower lock-in, and predictable pricing. Firebase wins for mobile-first apps tied to Google's ecosystem.
Both are mature open-source relational databases. Postgres has richer SQL (CTEs, window functions, JSON, arrays, extensions), stricter standards compliance, and better for complex analytics. MySQL is simpler, often faster on basic read-heavy workloads, and dominates WordPress/PHP ecosystems.
Not sure? Run both side by side — swap between them in your AI agent with a single config line.