About PostgreSQL & MongoDB: Why This Migration Matters

Before diving into the migration process, let’s understand the unique strengths of these two databases — and why businesses often need to bridge them:

What is PostgreSQL?

PostgreSQL (Postgres) is an enterprise-grade open-source relational database management system (RDBMS) renowned for its robustness, extensibility, and compliance with SQL standards. It uses tables, rows, and columns with rigid schemas, adhering to ACID (Atomicity, Consistency, Isolation, Durability) principles. Key use cases include:

Enterprise-level applications requiring advanced SQL features (CTEs, triggers, stored procedures)
Data warehousing and analytics (supports JSON/JSONB, spatial data, and full-text search)
Cloud deployments (Amazon RDS for PostgreSQL, Azure PostgreSQL, Google Cloud SQL)
Open-source ecosystems (Python/Java/Node.js integration)
Mission-critical systems with high data integrity requirements

PostgreSQL’s strengths lie in its open-source flexibility, advanced SQL capabilities, and enterprise-grade reliability. However, businesses often migrate to MongoDB for greater scalability with unstructured data, horizontal scaling, and modern cloud-native application development.

What is MongoDB?

MongoDB is a leading document-oriented NoSQL database designed for flexibility and scalability. It stores data in BSON (Binary JSON) documents, allowing dynamic schemas that adapt to evolving application requirements. Key use cases include:

Modern web/mobile apps with changing data models (user profiles, product catalogs)
Big data and real-time analytics (supports sharding for distributed scaling)
Cloud-native and microservices architectures
Agile development workflows requiring rapid iterations
Global distributed deployments (multi-region Atlas clusters)

MongoDB’s strengths include handling unstructured/semi-structured data, seamless horizontal scaling, and integration with modern development stacks. Migrating PostgreSQL data to MongoDB enables businesses to leverage these strengths while preserving valuable data from relational systems.

Why Migrate PostgreSQL to MongoDB?

Common scenarios for PostgreSQL-to-MongoDB migration include:

Modernizing open-source applications to cloud-native MongoDB deployments
Scaling beyond PostgreSQL’s vertical scaling limits for high-volume unstructured data
Unifying PostgreSQL’s structured data with MongoDB’s unstructured data for holistic analytics
Reducing operational overhead for non-transactional workloads
Integrating PostgreSQL data with MongoDB-based microservices architectures
Leveraging MongoDB Atlas for global distributed data deployments

Why Choose Our PostgreSQL to MongoDB Tool?

✅ Flexible Migration Modes - 4 import types to fit every use case: Query to Collection, 1 Table to 1 Collection, N Tables to 1 Collection, N Tables to N Collections.
✅ Blazing Fast Performance - Migrate millions of rows in minutes with optimized stream processing.
✅ Enterprise-Grade Compatibility - Works with all MongoDB deployment types and PostgreSQL versions (9.x/10/11/12/13/14/15/16, including Amazon RDS/Azure PostgreSQL).
✅ Secure & Local Processing - All data migration happens locally; no data is sent to third-party servers. Supports PostgreSQL SSL/TLS encryption.
✅ Cross-Platform Support - Consistent experience on Windows (10/11/Server), macOS (10.15+), and Linux (Debian/Ubuntu/Fedora/RHEL/openSUSE).
✅ Automated Scheduling - Set daily/weekly/monthly tasks via CLI for hands-free migration.
✅ Intuitive Configuration - Customize field mapping, JSONB to BSON conversion, and load types (Replace/Append) with ease.
✅ PostgreSQL Special Support - Handle Postgres-specific types (JSONB, ARRAY, hstore, TIMESTAMPTZ) and schemas.

4 Simple Steps to Migrate PostgreSQL to MongoDB

1. Connect to PostgreSQL & MongoDB

PostgreSQL Connection:
- Enter host address (e.g., localhost, rds-postgres01.xxxx.us-east-1.rds.amazonaws.com), port (5432), database name (e.g., postgres)
- Enter username/password (supports pg_hba.conf authentication)
- Enable SSL for secure connections (required for cloud Postgres deployments)
- Example connection: postgres@localhost:5432:adventureworks
MongoDB Connection: Configure URI (supports self-hosted instances and MongoDB Atlas).
Example URI: mongodb://localhost:27017/local or mongodb+srv://atlas_user:@cluster0.mongodb.net/

2. Select Migration Type & Data Source

Choose the perfect migration method for your needs:

Migration Type	Use Case	Example
Query to Collection	Export filtered data via custom PostgreSQL query	Extract sales data: `SELECT order_id, customer_id, order_date, total_amount FROM sales.orders WHERE order_date > '2023-01-01'`
1 to 1	Migrate one PostgreSQL table to one MongoDB collection	PostgreSQL `hr.employees` → MongoDB `employees`
N to 1	Combine multiple PostgreSQL tables into one collection	`sales.orders_2024` + `sales.order_2025` → MongoDB `orders`
N to N	Batch migrate tables to separate collections	`products`→`products`, `categories`→`categories`, `suppliers`→`suppliers`

3. Configure Migration Settings

Field Mapping: Map PostgreSQL columns to MongoDB collection fields (supports selective inclusion/exclusion).
Load Type: Choose "Replace" to overwrite existing data or "Append" to add new records.
Advanced Options:
- Convert PostgreSQL TIMESTAMPTZ to MongoDB timestamps (preserve time zones)
- Convert PostgreSQL JSONB/ARRAY/hstore to MongoDB BSON types
- Handle NULL values and serial/identity columns
- Set error tolerance and batch size
Preview Data: Verify up to 50 sample records before starting the migration.

4. Start Migration & Monitor Progress

Real-time progress tracking: View migration speed, success/failure count, and remaining time.
Example Results: 500,000 records migrated in 2.5 minutes, 1M records (5 tables) in 4 minutes.
Post-Migration: Click "View" to verify MongoDB collection data instantly.
Export migration report (CSV/JSON) for auditing and compliance.

Key Migration Features

Flexible Data Handling

Support for PostgreSQL-specific data types (JSONB, ARRAY, hstore, TIMESTAMPTZ, UUID, spatial data) and MongoDB’s document structure.
Automatic conversion of PostgreSQL schemas to dynamic MongoDB documents.
Include/exclude specific columns or tables for targeted migration.
Preview sample data to ensure mapping accuracy before migration.

Automation & Scheduling

Run migrations via intuitive GUI (step-by-step wizard) or CLI (for automation).
Create .bat (Windows) or .sh (Linux/macOS) scripts from saved sessions.
Schedule recurring tasks using Windows Task Scheduler, cron (Linux/macOS), or systemd.
Integration with CI/CD pipelines for DevOps workflows.

Error Resilience & Compliance

Configurable error tolerance (allow 0+ errors) with detailed error logging.
Comprehensive migration logs: Track migration history at C:\Users\{user_name}\AppData\Local\DBToMongo\{date}.log (Windows) or ~/.config/DBToMongo/{date}.log (Linux/macOS).
Partial migration recovery for large datasets.
Audit trails for compliance with GDPR, HIPAA, and SOX regulations.

Common Use Cases

Application Modernization: Migrate legacy PostgreSQL apps to MongoDB for cloud-native deployment (Atlas multi-region clusters).
Scalability: Scale horizontally with MongoDB to handle growing PostgreSQL datasets and global user bases.
Data Model Flexibility: Adapt structured PostgreSQL data to MongoDB’s dynamic documents for modern apps.
Cost Optimization: Reduce PostgreSQL cloud costs (RDS/Azure) by offloading non-transactional workloads to MongoDB.
Analytics & Insights: Combine PostgreSQL’s structured data with MongoDB’s unstructured data for holistic analytics.
Microservices Integration: Sync PostgreSQL data with MongoDB-based microservices architectures.

Migration Example: PostgreSQL Query to MongoDB Collection

Source Query: SELECT employee_id, first_name, last_name, job_title, department_id, hire_date FROM hr.employees WHERE department_id = 10

Target Collection: employees

Migration Result: 24 records migrated in 0.8 seconds.

employee_id	first_name	last_name	job_title	department_id	hire_date
1	Ken	Sanchez	Chief Executive Officer	10	2009-01-14 09:00:00+00
2	Terri	Duffy	Vice President of Engineering	10	2008-01-26 10:00:00+00
3	Roberto	Tamburello	Engineering Manager	10	2007-11-11 11:00:00+00
4	Rob	Walters	Senior Engineering Manager	10	2007-01-05 08:00:00+00
5	Gail	Erickson	Engineering Manager	10	2008-01-01 09:00:00+00
6	Jossef	Goldberg	Senior Design Engineer	10	2009-02-15 10:00:00+00

Frequently Asked Questions

Q: How long does PostgreSQL to MongoDB migration take?

A: Migration speed depends on dataset size, hardware, and network. The tool migrates millions of rows in minutes — 100,000 records take ~30 seconds, 1M records take ~2-3 minutes.

Q: Is the migration process secure?

A: Yes! All data is processed locally on your machine. No PostgreSQL or MongoDB credentials or data are transmitted to external servers. Supports PostgreSQL SSL/TLS encryption and MongoDB TLS/SSL.

Q: Can I migrate data from Amazon RDS PostgreSQL to MongoDB Atlas?

A: Absolutely! Enter your RDS PostgreSQL connection string (e.g.,

host=rds-postgres01.xxxx.us-east-1.rds.amazonaws.com port=5432 dbname=adventureworks user=postgres password=xxxx sslmode=require

) and MongoDB Atlas URI, then migrate directly between cloud services.

Q: Can I automate migrations via command line?

A: Yes! Save your migration session in the GUI, then run it via CLI on Windows, Linux, or macOS.

Q: What PostgreSQL and MongoDB versions are supported?

A: Supports PostgreSQL 9.x/10/11/12/13/14/15/16, Amazon RDS for PostgreSQL, Azure PostgreSQL, Google Cloud SQL for PostgreSQL; and MongoDB 3.x/4.x/5.x/6.x (all deployment types: standalone, replica sets, sharded clusters, Atlas).

Q: Does the tool support PostgreSQL schemas (not just public schema)?

A: Yes! The tool supports migration from all PostgreSQL schemas (e.g., hr, sales, analytics) and can preserve schema names in MongoDB collection names (e.g., hr_employees).

Ready to Migrate PostgreSQL to MongoDB Effortlessly?

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