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 MongoDb as a source connector (using Auth, or usually an API key)
2. set up DynamoDB 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 MongoDb

MongoDB is a popular open-source NoSQL database that stores data in a flexible, document-based format. It is designed to handle large volumes of unstructured data and is highly scalable, making it a popular choice for modern web applications. MongoDB uses a JSON-like format to store data, which allows for easy integration with web applications and APIs. It also supports dynamic queries, indexing, and aggregation, making it a powerful tool for data analysis. MongoDB is widely used in industries such as finance, healthcare, and e-commerce, and is known for its ease of use and flexibility.

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.
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Prerequisites

1. A MongoDb account to transfer your customer data automatically from.
2. A DynamoDB 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 MongoDb and DynamoDB, for seamless data migration.

When using Airbyte to move data from MongoDb to DynamoDB, it extracts data from MongoDb using the source connector, converts it into a format DynamoDB can ingest using the provided schema, and then loads it into DynamoDB via the destination connector.

This allows businesses to leverage their MongoDb data for advanced analytics and insights within DynamoDB, simplifying the ETL process and saving significant time and resources. For further insights into leveraging MongoDB data within DynamoDB for enhanced analytics and streamlined ETL processes, check out our comprehensive article on "DynamoDB vs MongoDB."

Methods to Move Data From Mongodb to Dynamodb

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

Method 1: Connecting Mongodb to Dynamodb using Airbyte.

Step 1: Set up MongoDb as a source connector

1. First, you need to have a MongoDB instance running and accessible from the internet. You will also need to have the necessary credentials to access the database.

2. In the Airbyte dashboard, click on "Sources" and then click on "New Source."

3. Select "MongoDB" from the list of available sources.

4. In the "Connection Configuration" section, enter the following information:
- Host: The hostname or IP address of your MongoDB instance.
- Port: The port number on which your MongoDB instance is running.
- Username: The username you use to access your MongoDB instance.
- Password: The password you use to access your MongoDB instance.
- Authentication Database: The name of the database where your authentication credentials are stored.

5. Click on "Test Connection" to ensure that Airbyte can connect to your MongoDB instance.

6. If the connection is successful, click on "Save" to save your MongoDB source configuration.

7. You can now create a new pipeline and select your MongoDB source as the input. You can then configure the pipeline to transform and load your data into your desired destination.

Step 2: Set up DynamoDB as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "DynamoDB" connector and click on it.
3. Click on the "Create new connection" button.
4. Enter a name for your connection and click on the "Next" button.
5. Enter your AWS access key ID and secret access key in the appropriate fields.
6. Enter the name of the DynamoDB table you want to connect to.
7. Choose the region where your DynamoDB table is located.
8. Click on the "Test connection" button to ensure that your credentials are correct and that the connection is successful.
9. If the test is successful, click on the "Create connection" button to save your settings.
10. You can now use the DynamoDB destination connector to transfer data from your source to your DynamoDB table.

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

Once you've successfully connected MongoDb as a data source and DynamoDB 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 MongoDb from the dropdown list of your configured sources.
3. Select your destination: Choose DynamoDB 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 MongoDb objects you want to import data from towards DynamoDB. 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 MongoDb to DynamoDB according to your settings.

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

Method 2: Connecting Mongodb to Dynamodb manually.

Moving data from MongoDB to Amazon DynamoDB without using connectors or integrations will require you to write custom scripts or use the native tools provided by the respective databases.

Prerequisites:

• MongoDB is installed and running with the data that needs to be migrated.
• AWS account with DynamoDB access.
• AWS CLI installed and configured with the necessary permissions.
• Knowledge of MongoDB and DynamoDB schema designs.

Step 1: Export Data from MongoDB

1. Identify the data in MongoDB that you want to migrate.
2. Use mongodump to export data from MongoDB. This tool can export data in a BSON format.
   
   mongodump --db your_database --collection your_collection --out /path/to/exported_data

Step 2: Convert BSON Data to JSON

Use bsondump, which is a utility that comes with MongoDB, to convert the BSON files to JSON.

bsondump /path/to/exported_data/your_database/your_collection.bson > /path/to/json_data/your_collection.json

Step 3: Transform the JSON Data (Optional)

1. The exported JSON might need to be transformed to match DynamoDB's data model and constraints (e.g., attribute name restrictions, data types, etc.).
2. Write a script or use a tool to transform the JSON data. For example, you can use jq or a custom Python script.

Step 4: Create a DynamoDB Table

1. Define the table schema for DynamoDB, including the primary key and any secondary indexes.
2. Create the table using the AWS Management Console, AWS CLI, or an AWS SDK. For example:

aws dynamodb create-table \

    --table-name NewDynamoDBTable \

    --attribute-definitions AttributeName=PrimaryKey,AttributeType=S \

    --key-schema AttributeName=PrimaryKey,KeyType=HASH \

    --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

Step 5: Import Data into DynamoDB

1. Write a script to read the transformed JSON data and insert it into the DynamoDB table.
2. You can use AWS SDKs (e.g., Boto3 for Python) to interact with DynamoDB.

Here's a simple Python script example using Boto3:

import boto3

import json

dynamodb = boto3.resource('dynamodb')

table = dynamodb.Table('NewDynamoDBTable')

with open('/path/to/json_data/your_collection.json', 'r') as file:

    items = json.load(file)

    for item in items:

        table.put_item(Item=item)

Step 6: Verify Data Integrity

1. After the import, verify that the data in DynamoDB is consistent with the original data in MongoDB.
2. You can perform random checks or write a script to compare counts and sample data between both databases.

Step 7: Clean up

1. Once the migration is complete and verified, clean up any temporary files or resources used during the process.

Important Considerations:

• Data Types: Ensure that the data types in MongoDB are compatible with DynamoDB data types, and convert them if necessary.
• Indexes: DynamoDB requires you to define primary keys and any global or local secondary indexes upfront. Make sure these are planned according to your query patterns.
• Throughput: Be mindful of the read/write throughput settings in DynamoDB to avoid throttling during the import process.
• Batch Operations: Consider using batch operations (batch_write_item) to speed up the data import process.
• Error Handling: Implement proper error handling in your scripts to deal with any issues during the data migration process.
• Security: Ensure that the data is handled securely throughout the migration process and that AWS credentials and permissions are managed correctly.

It's important to test the entire process with a subset of data before attempting to migrate the entire dataset.

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Use Cases to transfer your MongoDb data to DynamoDB

Integrating data from MongoDb to DynamoDB provides several benefits. Here are a few use cases:

1. Advanced Analytics: DynamoDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your MongoDb data, extracting insights that wouldn't be possible within MongoDb alone.
2. Data Consolidation: If you're using multiple other sources along with MongoDb, syncing to DynamoDB 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: MongoDb has limits on historical data. Syncing data to DynamoDB allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: DynamoDB provides robust data security features. Syncing MongoDb data to DynamoDB ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: DynamoDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding MongoDb data.
6. Data Science and Machine Learning: By having MongoDb data in DynamoDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While MongoDb provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to DynamoDB, providing more advanced business intelligence options. If you have a MongoDb table that needs to be converted to a DynamoDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a MongoDb account as an Airbyte data source connector.
2. Configure DynamoDB as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from MongoDb to DynamoDB 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!