Organizations often migrate from one database system to another to meet changing requirements or leverage new capabilities. One such migration path that has gained popularity is the transition from PostgreSQL, a robust relational database, to MongoDB, a flexible and scalable NoSQL database.

This article explores two methods for migrating PostgreSQL to MongoDB: using Airbyte, a modern data integration platform, and a manual approach utilizing PostgreSQL's COPY command and MongoDB's mongoimport tool. Whether you're looking for a streamlined, automated solution or prefer a hands-on approach, this guide will provide you with the knowledge to successfully migrate your data.

What is Postgres

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many webs, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What is MongoDB

MongoDB is a database that powers crucial applications and systems for global businesses. Designed for developers and specializing in the areas of open source, software development, and databases, it offers functionality such as horizontal scaling, automatic failover, and the capability to assign data to a location.

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Why migrate from PostgreSQL to MongoDB?

1. Schema flexibility: MongoDB's document model allows for dynamic schemas, enabling rapid iteration and easier handling of evolving data structures without migrations.

2. Scalability: MongoDB's horizontal scaling (sharding) is often simpler to implement than PostgreSQL's, particularly for distributed systems and high-volume data.

3. Performance for certain workloads: For read-heavy operations or when dealing with large volumes of unstructured data, MongoDB can outperform PostgreSQL.

4. JSON/BSON support: MongoDB's native JSON-like document storage aligns well with modern application development, especially for JavaScript-heavy stacks.

5. Use case alignment: For applications dealing with varied, rapidly changing data structures or requiring real-time analytics on large datasets, MongoDB's document model may be more suitable.

It's worth noting that migration decisions should be based on specific use cases, as PostgreSQL remains superior for many scenarios, especially those requiring complex transactions or joins.

Here are a few comments from Reddit about migrating from PostgreSQL to MongoDB:

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Source: Reddit

Methods to Move Data From Postgresql to Mongodb

• Method 1: Connecting Postgresql to Mongodb using Airbyte.
• Method 2: Connecting Postgresql to Mongodb manually.

Method 1: Connecting Postgresql to Mongodb using Airbyte.

Prerequisites

1. A Postgres account to transfer your customer data automatically from.
2. A MongoDB account.
3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Postgres and MongoDB, for seamless data migration.

When using Airbyte to move data from Postgres to MongoDB, it extracts data from Postgres using the source connector, converts it into a format MongoDB can ingest using the provided schema, and then loads it into MongoDB via the destination connector. This allows businesses to leverage their Postgres data for advanced analytics and insights within MongoDB, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Postgres as a source connector

1. Open your PostgreSQL database and create a new user with the necessary permissions to access the data you want to replicate.

2. Obtain the hostname or IP address of your PostgreSQL server and the port number it is listening on.

3. Create a new database in PostgreSQL that will be used to store the replicated data.

4. Obtain the name of the database you just created.

5. In Airbyte, navigate to the PostgreSQL source connector and click on "Create Connection".

6. Enter a name for your connection and fill in the required fields, including the hostname or IP address, port number, database name, username, and password.

7. Test the connection to ensure that Airbyte can successfully connect to your PostgreSQL database.

8. Select the tables or views you want to replicate and configure any necessary settings, such as the replication frequency and the replication method.

9. Save your configuration and start the replication process.

10. Monitor the replication process to ensure that it is running smoothly and troubleshoot any issues that arise.

Step 2: Set up MongoDB as a destination connector

Step 3: Set up a connection to sync your Postgres data to MongoDB

Once you've successfully connected Postgres as a data source and MongoDB as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select Postgres from the dropdown list of your configured sources.
3. Select your destination: Choose MongoDB from the dropdown list of your configured destinations.
4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
5. Select the data to sync: Choose the specific Postgres objects you want to import data from towards MongoDB. You can sync all data or select specific tables and fields.
6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Postgres to MongoDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MongoDB data warehouse is always up-to-date with your Postgres data.

Method 2: Connecting Postgresql to Mongodb manually.

Moving data from PostgreSQL to MongoDB manually can be a manual process that involves extracting data from PostgreSQL, transforming it into a format that MongoDB can ingest, and then importing it into MongoDB. Here's a step-by-step guide to accomplish this task:

Step 1: Export Data from PostgreSQL

1. Identify the Data to Export: Pick the tables or data you need to move from PostgreSQL to MongoDB.
2. Connect to PostgreSQL: Use the psql command-line tool or a PostgreSQL client to connect to your database.
   psql -h hostname -p port -U username -d databasename
3. Export Data: Use the COPY command in PostgreSQL to export the data to a CSV file.
   \COPY tablename TO 'path_to_csv_file.csv' WITH CSV HEADER;
4. Repeat this step for each table you want to export.

Step 2: Transform Data (If Necessary)

1. Analyze Data: Look at the data in the CSV files and decide how you want to structure it in MongoDB, which is document-oriented.
2. Transform Data: Write a script or use a spreadsheet program to transform the relational data into JSON documents. This might involve:some text
   • Combining data from multiple tables into a single document (denormalization).
   • Converting foreign keys into nested documents or arrays.
   • Changing date and time formats to ISO 8601 format, which MongoDB uses.

Step 3: Prepare MongoDB

1. Install MongoDB: If not already installed, download and install MongoDB from the official website.
2. Start MongoDB: Run the MongoDB server (mongod) on your system.
3. Create a Database & Collections: Connect to MongoDB using the mongo shell and create a new database and collections.
   use newdatabase

db.createCollection("newcollection")

4. Repeat the collection creation for each type of data you are importing.

Step 4: Import Data into MongoDB

1. Convert CSV to JSON: Use a conversion tool or write a script to convert your CSV files to JSON format. Make sure the JSON structure matches the MongoDB collections you've created.
2. Import JSON Data: Use the mongoimport tool to import the JSON files into the appropriate MongoDB collections.
   mongoimport --db newdatabase --collection newcollection --file 'path_to_json_file.json'
3. Repeat this step for each JSON file corresponding to a MongoDB collection.

Step 5: Verify Data Integrity

1. Check Counts: Compare the number of records in PostgreSQL and MongoDB to ensure they match.
2. Sample Data: Query a few documents from MongoDB and compare them with the original data in PostgreSQL to verify that the transformation and import processes worked correctly.

Step 6: Clean Up

1. Backup: Make sure to back up your original PostgreSQL data before decommissioning any servers or services.
2. Remove Temporary Files: Delete any intermediate CSV or JSON files if they are no longer needed.

Tips:

• Always perform these operations in a test environment before moving to production.
• Consider indexing your MongoDB collections after the import to optimize query performance.
• Test your application against the new MongoDB data to ensure compatibility.
• Monitor MongoDB performance and adjust the schema or indexing strategy as needed.

Remember that the complexity of this process can vary greatly depending on the structure and size of your data, and it might require custom scripting to handle complex transformations.

Use Cases to transfer your Postgres data to MongoDB

Integrating data from Postgres to MongoDB provides several benefits. Here are a few use cases:

1. Advanced Analytics: MongoDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Postgres data, extracting insights that wouldn't be possible within Postgres alone.
2. Data Consolidation: If you're using multiple other sources along with Postgres, syncing to MongoDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: Postgres has limits on historical data. Syncing data to MongoDB allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: MongoDB provides robust data security features. Syncing Postgres data to MongoDB ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: MongoDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Postgres data.
6. Data Science and Machine Learning: By having Postgres data in MongoDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While Postgres provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MongoDB, providing more advanced business intelligence options. If you have a Postgres table that needs to be converted to a MongoDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a Postgres account as an Airbyte data source connector.
2. Configure MongoDB as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from Postgres to MongoDB after you set a schedule

For further insights, consider exploring an informative article detailing the migration process from MongoDB to Postgres.

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

FAQs

1. Can we use PostgreSQL and MongoDB together?

Yes, PostgreSQL and MongoDB can be used together in a polyglot persistence architecture. This approach leverages the strengths of both databases: PostgreSQL for structured data and complex transactions, and MongoDB for flexible, schema-less data and horizontal scalability. Organizations often implement this hybrid model to optimize different parts of their application, using each database for the workloads it handles best. However, this strategy requires careful design to maintain data consistency and may increase operational complexity.

2. Is MongoDB better than PostgreSQL?

Neither MongoDB nor PostgreSQL is universally "better." Each excels in different scenarios. MongoDB shines with flexible schemas and horizontal scaling for certain use cases, while PostgreSQL offers robust ACID compliance and complex querying capabilities. The choice depends on specific project requirements, data structures, and scalability needs.

3. Why MongoDB is so popular?

MongoDB's popularity stems from its flexible document model, which aligns well with modern application development practices. Its ease of use, horizontal scalability, and native support for JSON-like data structures make it attractive for rapid development cycles and handling large volumes of unstructured or semi-structured data.

4. How to replicate data from PostgreSQL to MongoDB?

Replicating data from PostgreSQL to MongoDB can be achieved using change data capture (CDC) tools or ETL processes. One efficient solution is Airbyte, an open-source data integration platform. Airbyte provides pre-built connectors for both PostgreSQL and MongoDB, allowing you to set up a replication pipeline with minimal configuration, handling both initial data loads and ongoing synchronization.