How to Migrate Data from MongoDB to PostgreSQL: 2 Easy Methods

MongoDB excels when data is unstructured and schemas change frequently. But as applications scale, that flexibility can become a limitation. Complex joins turn into expensive aggregation pipelines, reporting tools expect SQL, and analytics queries become harder to optimize.

This is often the point at which teams begin evaluating PostgreSQL.

PostgreSQL is now used by 49% of developers, making it the most popular database. Its combination of full SQL support, strict ACID compliance, JSONB for semi-structured data, and a mature extension ecosystem makes it a practical long-term destination.

The challenge is that MongoDB stores data as flexible, nested BSON documents, while PostgreSQL relies on structured tables and defined data types. Successful migration requires thoughtful schema design, not just data transfer.

This post covers two migration approaches: a no-code method using Hevo for automated, continuous sync and a manual method using mongoexport and psql. You’ll also see a side-by-side comparison to help choose the right approach for your needs.

What are the critical differences between MongoDB and PostgreSQL

MongoDB and PostgreSQL take fundamentally different approaches to storing and managing data. Understanding these differences is essential when deciding how to model your data and when planning a migration.

Here are the key distinctions:

Together, these differences shape how each database performs, scales, enforces consistency, and adapts to changing application needs.

If you want a deeper comparison, check out this blog: MongoDB vs PostgreSQL

MongoDB and PostgreSQL Data Integration

Migrating or synchronizing data between MongoDB and PostgreSQL is a common requirement for teams shifting from a flexible, document-oriented system toward the relational consistency and analytical power of PostgreSQL. Depending on your operational needs, this can be done in two main scenarios:

1. One-Time Migration

Used when a team is permanently moving application data from MongoDB to PostgreSQL.
This typically involves:

• Exporting collections
• Transforming nested documents into relational structures
• Loading data into PostgreSQL tables
  A one-time migration is usually performed when modernizing an application or consolidating data infrastructure.

2. Ongoing Replication or Continuous Sync

Here, MongoDB acts as the source of truth, and PostgreSQL is continuously updated with changes.
This is useful for:

• Analytics workloads
• Reporting dashboards
• ELT/ETL pipelines
• Hybrid architectures where MongoDB is transactional and PostgreSQL is analytical

In these cases, new inserts, updates, or deletes in MongoDB need to be captured and reflected in PostgreSQL with minimal delay.

Prerequisites for Migrating MongoDB to PostgreSQL 

Before you start the migration, make sure both databases are properly configured and accessible. Skipping this step is the most common reason migrations fail halfway through.

MongoDB Requirements

Version: Use MongoDB 6.0 or later. MongoDB 4.4 reached end-of-life in February 2024 and no longer receives security patches. If you are running an unsupported MongoDB version, upgrade before starting the migration.

For ongoing replication using change data capture, your MongoDB deployment must have a replica set enabled. Change Streams, which Hevo uses to capture inserts, updates, and deletes in real time, require replica set oplog access. A standalone MongoDB instance will not work for CDC-based sync.

Access and permissions: The database user you connect with needs at minimum:

• read on the source database
• readAnyDatabase if you are migrating across multiple databases
• clusterMonitor if you are enabling change data capture

Network: Your MongoDB host must be reachable from the migration tool or the machine running the export. If you are on MongoDB Atlas, whitelist the relevant IP address in the Network Access settings. For self-hosted MongoDB, confirm the port (default: 27017) is open and not blocked by a firewall rule.

PostgreSQL Requirements

Version: Use PostgreSQL 13 or later. PostgreSQL 12 reached end-of-life in November 2024. PostgreSQL 16 is the current stable release and the recommended target for new migrations.

Access and permissions: The PostgreSQL user used for the migration needs:

• CREATE and INSERT privileges on the target database
• USAGE on the target schema (default: public)
• If you are using Hevo, the destination user also needs SELECT on system catalog tables for schema introspection

Schema planning: Define your target schema before you start loading data. MongoDB’s BSON documents often contain nested objects and arrays. Decide upfront whether you will flatten these into separate tables or store them as JSONB columns in PostgreSQL. Changing this after a bulk load is painful.

Tools and Environment

Requirement	For Manual Migration	For Hevo (Automated ELT)
mongoexport installed	Yes (part of MongoDB Database Tools)	Not required
psql or PostgreSQL client	Yes	Not required
Hevo account	No	Yes: Start free
Replica set enabled on MongoDB	Only if doing CDC	Required for ongoing sync
Network access between source and destination	Yes	Yes. Hevo connects over TLS
CSV or JSON staging location	Yes	Not required

A Note on Data Volume

Depending on your transformation workflow, manual migrations may require large intermediate files or memory-intensive processing steps, especially when handling nested documents at scale. If your collection exceeds a few hundred MB, this will be slow and potentially unstable. 

One engineer who documented a 300GB migration on Medium noted their script crashed repeatedly until they switched to streaming the data in batches rather than loading it all at once.

For collections above 1GB, use batched exports by splitting on a field like _id or a timestamp, or use Hevo’s data pipeline to handle volume automatically.

Comparing the 2 Methods: Which Is Best for You? 

Both methods can get you from MongoDB to PostgreSQL. The right one depends on your team’s technical expertise, scalability needs, and migration timeline.

Here’s how they compare on the factors that matter most.

Criteria	Hevo (Automated ELT)	Manual (mongoexport + psql)
Setup time	Under 5 minutes	Hours to days
Coding required	None	SQL, shell, Python
Data volume	Any volume	Best under ~1GB
Continuous sync (CDC)	Yes, real-time	No, manual re-export each time
Schema mapping	Automatic	Manual, field by field
Type conversion & nesting	Automatic	Manual, error-prone
Error handling	Automatic retries + logging	Manual diagnosis, load stops on failure
Downtime at cutover	None	Yes, source must be quiesced
Cost	Subscription	Free tooling, engineering time

How to Choose

Use Hevo if:

• Your dataset is large, growing, or changes frequently
• You need ongoing sync rather than a one-time copy
• Your MongoDB collections have deeply nested documents or inconsistent field structures
• You cannot afford downtime or data gaps during migration
• You want full pipeline visibility without building monitoring infrastructure yourself

Use the manual method if:

• You are migrating a small, static dataset (a few hundred MB or less)
• This is a one-time operation with no ongoing sync requirement
• Your schema is flat and well-understood 
• You have the engineering time to handle edge cases and re-runs

A Note on Hybrid Approaches

Some teams use the manual method for an initial exploratory migration, to validate the schema design and catch edge cases in the data, then switch to Hevo for production-grade ongoing sync. This is a reasonable pattern, especially when moving from a legacy MongoDB setup where the document structure isn’t fully documented.

The manual export also gives you a local snapshot of the data at a point in time, which can serve as a backup before cutting over to the automated pipeline.

How to move data from MongoDB to PostgreSQL

Method 1: Using Hevo (No-Code Tool)

Hevo lets you transfer data from MongoDB to PostgreSQL automatically, no coding, no commands. Just follow these simple steps.

Step 1: Add MongoDB as Your Source

1. Log in to your Hevo Dashboard.
2. Click on “+ Create Pipeline” at the top right.
3. Under “Choose Source Type”, select MongoDB.
4. Enter your MongoDB connection details – this includes the hostname, port, database name, username, and password.
5. Test the connection, then click “Continue”.

Step 2: Add PostgreSQL as Your Destination

1. Now go to the Destination section in the pipeline setup.
2. Choose PostgreSQL as your destination type.
3. Fill in your PostgreSQL connection details – host, port, database name, username, and password.
4. Click “Test Connection” to make sure it works, then hit “Save Destination”.

Step 3: Configure Your Pipeline

1. Once source and destination are set, Hevo will guide you to the Data Mapping screen.
2. Here, you can let Hevo auto-map the fields from MongoDB to PostgreSQL, or manually adjust the schema as needed.
3. Use the Data Transformations option if you want to clean or reshape your data before loading.

Step 4: Activate and Run

1. Review the pipeline summary and click “Activate Pipeline”.
2. Hevo will now begin transferring data from MongoDB to PostgreSQL in real time.
3. You can monitor progress from the Pipeline Dashboard, and even set up alerts or logs to track updates.

Method 2: Manual Migration (Do It Yourself)

This method is great for small projects or for those who want full control. It follows the ETL method, which stands for Extract, Transform, and Load.

What’s Needed Before Starting

• MongoDB is installed (Version 4.4 works well).
• PostgreSQL installed (Version 12 or higher).
• A terminal or command line tool to type commands.
• A place on the computer to save a file in CSV format.

Step 1: Export Data from MongoDB

MongoDB has a tool called mongoexport. This tool pulls data from the database and saves it into a CSV file.

Here’s an example command to run in the terminal:

mongoexport --host localhost --db bookdb --collection books --type=csv --out books.csv --fields name,author,country,genre

This command creates a file called books.csv with the listed fields from the books collection in the bookdb database.

Step 2: Create a Table in PostgreSQL

A table needs to be made in PostgreSQL that matches the data from MongoDB. This way, the data knows where to go.

Here’s the SQL command to create the table:

CREATE TABLE books (id SERIAL PRIMARY KEY,  name VARCHAR NOT NULL,  author VARCHAR NOT NULL,  country VARCHAR NOT NULL,  genre VARCHAR NOT NULL);

Each column matches the fields in the CSV file from MongoDB.

Step 3: Import the Data into PostgreSQL

Now it’s time to move the data into PostgreSQL using the COPY command.

Here’s what the command looks like:

COPY books(name,author,country,genre)FROM 'C:/path/to/books.csv' DELIMITER ',' CSV HEADER;

This command tells PostgreSQL to load data from the CSV file into the books table.

Manual Method: Pros and Cons

Pros:

• Works well for small projects with limited data.
• No need for extra tools, just basic scripts or commands.

Cons:

• It can be confusing if you’re not familiar with databases or scripting.
• Easy to make mistakes like typos or missing schema details.
• Gets slow with large data volumes.

Performance Monitoring and Verification Post-Migration

The migration is not complete when the last row loads. You still need to confirm row counts match, query performance is acceptable, and no silent type conversion errors crept in during the transfer.

Use an ELT pipeline: For ongoing sync, Hevo handles data transformation and replication automatically. For custom scripts, batch your operations and build in retry logic. 

For a structured verification checklist, MongoDB’s Relational Migrator data verification guide covers the key checks in detail.

How to choose the right method in moving data from MongoDB to PostgreSQL?

When deciding how to migrate your data from MongoDB to PostgreSQL, the choice largely depends on your specific needs, technical expertise, and project scale.

• Manual Method: If you prefer granular control over the migration process and are dealing with smaller datasets, the manual ETL approach is a solid choice. This method allows you to manage every step of the migration, ensuring that each aspect is tailored to your requirements.
• Hevo Data: If simplicity and efficiency are your top priorities, Hevo Data’s no-code platform is perfect. With its seamless integration, automated schema mapping, and real-time transformation features, Hevo Data offers a hassle-free migration experience, saving you time and reducing the risk of errors.

Conclusion

You now have two proven ways to migrate MongoDB to PostgreSQL: automated ELT via Hevo for ongoing, production-grade sync, and manual export via mongoexport and psql for lightweight one-time transfers. The comparison table in the previous section tells you which fits your situation. 

If you are ready to connect MongoDB to PostgreSQL without writing migration scripts, start your free Hevo trial and have your first pipeline running in under 30 minutes.

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