MongoDB Atlas excels at storing and processing unstructured and semi-structured data, while PostgreSQL offers scalability and advanced analytics. MongoDB Atlas to PostgreSQL integration forms a robust ecosystem that addresses the technical challenges associated with data management and analysis.

In this guide, we will explore two easy methods for MongoDB Atlas to PostgreSQL Data Migration. Let’s dive in!

How to Connect MongoDB Atlas to PostgreSQL?


  • An active MongoDB Atlas account
  • MongoDB Compass
  • Access to MongoDB Atlas Cluster
  • An active PostgreSQL account

Method 1: Move Data from MongoDB Atlas using CSV files

Step 1: Connect MongoDB Atlas to MongoDB Compass

  • Log in to your MongoDB Atlas account. 
  • Select the desired cluster and click on Connect. Now, select I have MongoDB Compass, Compass version, and copy the Connection string

The Connection string includes crucial information like Database name, Collection name, Username, and Password. Replace <username> and <password> with your actual username and password.

MongoDB Atlas to PostgreSQL: Connect to Cluster
Image Source
  • Open MongoDB Compass and paste the modified connection string. Now, click the connect button to establish a connection between MongoDB Atlas and MongoDB Compass.

Step 2: Export Data Using MongoDB Compass

  • Open MongoDB Compass, move to the desired cluster’s database and choose a specific collection from which you want to export data.
  • Now, click the Export button located at the top right of the screen.
MongoDB Atlas to PostgreSQL: Export Data using MongoDB Compass
Image Source
  • A pop-up widget will appear, allowing you to select either JSON or CSV file format and specify the file location to save the exported document. In this case, we selected the CSV file format and clicked the Export button to initiate the export process.

Step 3: Load Data to PostgreSQL

  • You can easily create a PostgreSQL table using pgAdmin’s interface. Open pgAdmin and find the Tables option in the left-side menu under the Schema section. Right-click on Tables and select the Create option to create a new table.
MongoDB Atlas to PostgreSQL: Load Data to PostgreSQL using pgAdmin
Image Source
  • You can provide the table’s information, like its name and column names. Click the Save button to create a new table.
  • Right-click on the created table and choose Import/Export. Now, select your CSV file, choose the Export option, and click the OK button.
MongoDB Atlas to PostgreSQL: Export Data from MongoDB in pgAdmin
Image Source

You have successfully connected your MongoDB Atlas data to PostgreSQL. Here are a couple of benefits of using this approach:

  • Data Transformation Flexibility: Using CSV files grants you greater flexibility in performing direct custom modifications on the exported data. This includes tasks such as data cleaning, filtering, and transformation before loading it into PostgreSQL.
  • One-Time Data Transfer: Using CSV files is well-suited for performing one-time data migrations between databases. It offers a straightforward and effective solution to replicate data from MongoDB Atlas to PostgreSQL. By eliminating the requirement for complex automated processes, it minimizes overall migration expenses and streamlines the MongoDB Atlas to PostgreSQL integration process.

Migrating data from MongoDB Atlas to PostgreSQL comes with several benefits, but it’s essential to be aware of the potential drawbacks. Here are the key ones:

  • Time-Consuming: Using CSV files can be time-consuming and resource-intensive, especially when dealing with larger datasets. Since each step is performed manually, it requires individual attention, leading to potential time delays and the possibility of errors.
  • Security Concerns: Exporting and importing data using CSV files without proper security measures can pose significant risks, especially when handling sensitive or confidential data. It is essential to implement proper measures to ensure data protection throughout the data migration process.
  • Real-Time Data Synchronization: Using CSV files for replication requires manual intervention and execution of data transfers at regular intervals, leading to delays in data updates and potential inconsistencies between the two databases. As a result, any changes made in MongoDB Atlas are not immediately reflected in PostgreSQL.

Method 2: Automating the Data Replication Process using a No Code Tool

Automating the data replication process using a no-code tool enables you to experience significant advantages over the using CSV files approach. Here are some of them:

  • Streamlined Workflow: Using a no-code tool for MongoDB Atlas to PostgreSQL migration streamlines the workflow. No-code tools offer ready-to-use pre-built connectors, eliminating the need for complex coding. This allows for effortless setup of automated workflows.
  • Real-Time Replication: No-code tools provide both batch and real-time replication capabilities. This ensures that target databases are continuously updated with the latest information, resulting in a seamless and efficient data synchronization process.
  • User-Friendly: No-code tools are user-friendly, allowing non-technical users to effortlessly manage data replication tasks. With no-code tools setting up connections between databases doesn’t require coding, making data synchronization efficient and straightforward.

Hevo Data is a popular and widely used no-code data integration tool that simplifies connecting data from different sources, including MongoDB Atlas and PostgreSQL. It offers an all-in-one solution for extracting, loading, and transforming your data. With Hevo Data, you can easily connect your data sources and handle the entire data integration process without complex coding.

To perform the data migration from MongoDB Atlas to PostgreSQL, follow these steps:

Step 1: Configure Source

MongoDB Atlas to PostgreSQL: Configure MongoDB Atlas as a Source
Image Source

Step 2: Configure Destination

MongoDB Atlas to PostgreSQL: Configure PostgreSQL as a Destination
Image Source

You have successfully connected MongoDB Atlas to PostgreSQL. Now you can start analyzing your MongoDB Atlas data using the powerful capabilities of PostgreSQL.

What can you Achieve by Migrating Data from MongoDB Atlas to PostgreSQL?

Here’s what data analysts can do after MongoDB Atlas to PostgreSQL data replication.

  • Aggregate the data of individual interaction of the product for any event. 
  • Finding the customer journey within the product (website/application).
  • Integrating transactional data from different functional groups (Sales, marketing, product, Human Resources) and finding answers. For example:
    • Which Development features were responsible for an App Outage in a given duration?
    • Which product categories on your website were most profitable?
    • How does the Failure Rate in individual assembly units affect Inventory Turnover?

Additional Resources for MongoDB Integrations and Migrations


Migrating data from MongoDB Atlas to PostgreSQL offers several benefits, including data centralization, scalability, and improved performance. Using CSV files provides greater control, flexibility, and supports custom data transformations. However, it does come with certain limitations, including being time-consuming, lack of real-time synchronization, and raising data security concerns.

Alternatively, using a no-code tool like Hevo Data simplifies the MongoDB Atlas to PostgreSQL integration process. It offers a user-friendly interface and pre-built connectors, making the entire migration process easier for you. With real-time data streaming and transformation capabilities, you can seamlessly migrate data from MongoDB Atlas to PostgreSQL.

If you don’t want SaaS tools with unclear pricing that burn a hole in your pocket, opt for a tool that offers a simple, transparent pricing model. Hevo has 3 usage-based pricing plans starting with a free tier, where you can ingest up to 1 million records.

Schedule a demo to see if Hevo would be a good fit for you, today!

Tejaswini Kasture
Freelance Technical Content Writer, Hevo Data

Tejaswini's profound enthusiasm for data science and passion for writing drive her to create high-quality content on software architecture, and data integration.

All your customer data in one place.