This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

1. set up DynamoDB as a source connector (using Auth, or usually an API key)
2. set up MongoDB as a destination connector
3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is DynamoDB

Amazon DynamoDB is a fully managed proprietary NoSQL database service that supports key–value and document data structures and is offered by Amazon.com as part of the Amazon Web Services portfolio. DynamoDB exposes a similar data model to and derives its name from Dynamo, but has a different underlying implementation.

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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Prerequisites

1. A DynamoDB 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 DynamoDB and MongoDB, for seamless data migration.

When using Airbyte to move data from DynamoDB to MongoDB, it extracts data from DynamoDB 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 DynamoDB data for advanced analytics and insights within MongoDB, simplifying the ETL process and saving significant time and resources. Explore our in-depth article on 'DynamoDB vs MongoDB' to discover how businesses can harness DynamoDB data for advanced analytics within MongoDB, streamlining the ETL process and optimizing time and resource efficiency.

Methods to Move Data From Dynamodb to mongodb

• Method 1: Connecting Dynamodb to mongodb using Airbyte.
• Method 2: Connecting Dynamodb to mongodb manually.

Method 1: Connecting Dynamodb to mongodb using Airbyte

Step 1: Set up DynamoDB as a source connector

Step 2: Set up MongoDB as a destination connector

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

Once you've successfully connected DynamoDB 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 DynamoDB 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 DynamoDB 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 DynamoDB 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 DynamoDB data.

Method 2: Connecting Dynamodb to mongodb manually

Moving data from Amazon DynamoDB to MongoDB without third-party connectors involves several steps, including extracting data from DynamoDB, transforming it into a suitable format for MongoDB, and then importing it into MongoDB. Below is a detailed step-by-step guide to accomplish this task:

Step 1: Set Up Your Environment

1. Install AWS CLI: Make sure you have the AWS Command Line Interface (CLI) installed and configured with the necessary permissions to access your DynamoDB tables.

2. Install MongoDB: Ensure that MongoDB is installed on your server or local machine where you want to import the data. Also, make sure you have the `mongoimport` tool, which comes with MongoDB.

3. Install Python (Optional): If you plan to use a script to extract and transform the data, Python is a good choice due to its rich set of libraries for working with both AWS services and data transformation.

4. Install Required Libraries (Optional): If using Python, install the `boto3` library for interacting with AWS services and `pymongo` for MongoDB.

   ```bash

   pip install boto3 pymongo

   ```

Step 2: Export Data from DynamoDB

1. Scan or Query DynamoDB Table: Use the `aws dynamodb scan` command to export the entire table or `aws dynamodb query` for specific items. For large tables, consider using the `--page-size`, `--max-items`, or `--starting-token` parameters to paginate results.

   ```bash

   aws dynamodb scan --table-name YourDynamoDBTableName --page-size 100 --output json > dynamodb_data.json

   ```

2. Handle Large Data Sets: If your table is large, you may need to write a script to handle the scan operation and manage pagination. AWS SDKs like `boto3` in Python can help with this.

Step 3: Transform Data for MongoDB

1. Convert Data to MongoDB Format: DynamoDB and MongoDB have different data models. You'll need to transform the JSON data from DynamoDB into a format that MongoDB can understand. This typically involves mapping DynamoDB types to MongoDB types.

2. Write a Transformation Script (Optional): If the data requires complex transformations, write a script to process the exported JSON file and convert it into the proper format for MongoDB. Here's a high-level example using Python:

   ```python

   import json

   # Load the DynamoDB data exported as JSON

   with open('dynamodb_data.json', 'r') as file:

       dynamodb_data = json.load(file)

   # Transform the data to MongoDB format

   mongodb_data = []

   for item in dynamodb_data['Items']:

       mongodb_item = transform_to_mongodb_format(item)  # Implement this function based on your data

       mongodb_data.append(mongodb_item)

   # Save the transformed data to a new JSON file

   with open('mongodb_data.json', 'w') as file:

       json.dump(mongodb_data, file)

   ```

Step 4: Import Data into MongoDB

1. Use `mongoimport` to Import Data: With the data transformed into a MongoDB-friendly format, use the `mongoimport` tool to import the data into your MongoDB database.

   ```bash

   mongoimport --db YourMongoDBDatabase --collection YourMongoDBCollection --file mongodb_data.json

   ```

2. Verify the Data: After the import is complete, connect to your MongoDB database and verify that the data has been imported correctly.

   ```bash

   mongo YourMongoDBDatabase

   db.YourMongoDBCollection.find().limit(10)

   ```

Step 5: Clean Up

1. Remove Temporary Files: If you created any temporary files during the transformation process, remember to delete them if they are no longer needed.

2. Review Security: Ensure that any scripts or tools used in the process follow best security practices, such as not hardcoding credentials.

Additional Tips

• Backup Your Data: Always back up your DynamoDB data before starting the migration process to prevent data loss.
• Monitor Throughput: Keep an eye on read/write throughput on both DynamoDB and MongoDB to avoid throttling.
• Test the Process: Run a test migration with a subset of the data to ensure that everything works as expected before performing the full migration.

By following these steps, you should be able to migrate data from DynamoDB to MongoDB without using third-party connectors or integrations. Remember to tailor the transformation script to your specific data schema and requirements.

Use Cases to transfer your DynamoDB data to MongoDB

Integrating data from DynamoDB 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 DynamoDB data, extracting insights that wouldn't be possible within DynamoDB alone.
2. Data Consolidation: If you're using multiple other sources along with DynamoDB, 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: DynamoDB 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 DynamoDB 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 DynamoDB data.
6. Data Science and Machine Learning: By having DynamoDB data in MongoDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While DynamoDB 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 DynamoDB 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 DynamoDB 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 DynamoDB to MongoDB after you set a schedule

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!