Does PostgreSQL Work With MongoDB?

Partially CompatibleLast verified: 2026-02-26

PostgreSQL and MongoDB can be used together in the same application, but they serve different purposes and require deliberate architectural decisions to integrate effectively.

Quick Facts

Compatibility

partial

Setup Difficulty

Moderate

Official Integration

No — community maintained

Confidence

high

Minimum Versions

PostgreSQL: 10.0

MongoDB: 3.6

How PostgreSQL Works With MongoDB

PostgreSQL and MongoDB aren't directly integrated—they're separate database systems that coexist in a polyglot persistence architecture. You'd typically use PostgreSQL for relational data requiring ACID compliance (users, transactions, structured business logic) and MongoDB for flexible document storage (logs, user profiles, semi-structured content). Both databases connect independently through their respective drivers (psycopg2 for PostgreSQL, pymongo for MongoDB) within the same application. This approach works well when you have clear domain boundaries: PostgreSQL handles normalized, transactional data while MongoDB handles denormalized, schemaless collections. The main challenge is maintaining data consistency across both systems—there's no built-in mechanism to synchronize transactions between them. You'll need application-level logic or event-driven architecture (e.g., publishing events to sync changes) to keep data coherent. ORMs like SQLAlchemy (PostgreSQL) and ODMs like MongoEngine (MongoDB) can coexist in the same codebase, though you're managing two separate connections and migration strategies.

Best Use Cases

→SaaS platforms storing structured user/billing data in PostgreSQL while keeping flexible audit logs and activity feeds in MongoDB

→E-commerce systems using PostgreSQL for orders and inventory, MongoDB for product catalogs with varying attributes

→Analytics platforms with PostgreSQL for transactional data and MongoDB for time-series event collections

→Content management systems storing pages and metadata in PostgreSQL with flexible JSON documents in MongoDB

Polyglot Persistence with PostgreSQL and MongoDB

bash

pip install psycopg2-binary pymongo

python

import psycopg2
from pymongo import MongoClient
from datetime import datetime

# PostgreSQL for user accounts
pg_conn = psycopg2.connect("dbname=myapp user=postgres password=secret")
pg_cursor = pg_conn.cursor()
pg_cursor.execute("INSERT INTO users (email, created_at) VALUES (%s, %s)",
                  ('user@example.com', datetime.now()))
pg_conn.commit()

# MongoDB for activity logs
mongo_client = MongoClient('mongodb://localhost:27017/')
db = mongo_client['myapp']
activity_collection = db['activity_logs']
activity_collection.insert_one({
    'user_id': 1,
    'action': 'login',
    'timestamp': datetime.now(),
    'metadata': {'ip': '192.168.1.1', 'browser': 'Chrome'}
})

pg_cursor.close()
pg_conn.close()
mongo_client.close()

Known Issues & Gotchas

critical

No cross-database transactions or joins between PostgreSQL and MongoDB

Fix: Design schema boundaries carefully. Use application-level orchestration or event sourcing to maintain consistency. Avoid queries that need to join data across both databases.

warning

Duplicate data and synchronization complexity when the same entity exists in both databases

Fix: Establish a single source of truth for each entity. Use MongoDB for read-heavy denormalized copies and PostgreSQL as the authoritative store, or vice versa. Implement async sync mechanisms.

warning

Increased operational overhead managing two separate databases, backups, and monitoring

Fix: Use managed services (AWS RDS, MongoDB Atlas) to reduce operational burden. Document which data lives where clearly.

info

Developer confusion about which database to query for a given piece of data

Fix: Create clear data ownership documentation and enforce it through code reviews. Consider a data catalog or internal wiki.

Alternatives

•PostgreSQL with JSONB columns (single database, flexible schema without separate NoSQL store)
•MongoDB with relational plugins or application-level normalization (single document database, avoids dual-database complexity)
•DynamoDB + PostgreSQL (if targeting AWS; managed NoSQL + relational on cloud-native stack)

Resources

docsPostgreSQL Official Documentation docsMongoDB Official Documentation tutorialPolyglot Persistence Pattern - Martin Fowler docsPyMongo Driver Documentation

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