How to load data from MongoDb to S3 Glue

Learn how to use Airbyte to synchronize your MongoDb data into S3 Glue within minutes.

Try Airbyte Cloud

Get a demo

Building your pipeline or Using Airbyte

Airbyte is the only open solution empowering data teams to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:

Reliable and accurate
Extensible and scalable for all your needs
Deployed and governed your way

All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a MongoDb connector in Airbyte

Connect to MongoDb or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up S3 Glue for your extracted MongoDb data

Select S3 Glue where you want to import data from your MongoDb source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the MongoDb to S3 Glue in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Try Airbyte Cloud

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Old Automated Content

TL;DR

set up MongoDb as a source connector (using Auth, or usually an API key)
set up S3 Glue as a destination connector
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 S3 Glue

S3 Glue is a server less, salable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application development. It provides all the capabilities required for data integration, so you can get insights and put your data to use in minutes instead of months. With S3 Glue, there is no infrastructure to set up or manage. You can pay only for the resources consumed while your jobs are continuing.

Integrate MongoDb with S3 Glue in minutes

Try for free now

Prerequisites

A MongoDb account to transfer your customer data automatically from.
A S3 Glue account.
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 S3 Glue, for seamless data migration.

When using Airbyte to move data from MongoDb to S3 Glue, it extracts data from MongoDb using the source connector, converts it into a format S3 Glue can ingest using the provided schema, and then loads it into S3 Glue via the destination connector. This allows businesses to leverage their MongoDb data for advanced analytics and insights within S3 Glue, simplifying the ETL process and saving significant time and resources.

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 S3 Glue as a destination connector

1. Log in to your Airbyte account and navigate to the "Destinations" tab.
2. Click on "Add Destination" and select "S3 Glue" from the list of available connectors.
3. Enter your AWS access key ID and secret access key in the appropriate fields.
4. Select the AWS region where you want to store your data.
5. Enter the name of the S3 bucket where you want to store your data.
6. Choose the format in which you want to store your data (e.g. CSV, JSON, Parquet).
7. Enter the prefix for your data files (e.g. "mydata/").
8. Choose whether you want to compress your data files (e.g. Gzip).
9. Click on "Test Connection" to ensure that Airbyte can connect to your S3 Glue destination.
10. If the connection is successful, click on "Save" to save your S3 Glue destination configuration.

Step 3: Set up a connection to sync your MongoDb data to S3 Glue

Once you've successfully connected MongoDb as a data source and S3 Glue as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select MongoDb from the dropdown list of your configured sources.
Select your destination: Choose S3 Glue from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific MongoDb objects you want to import data from towards S3 Glue. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from MongoDb to S3 Glue according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your S3 Glue data warehouse is always up-to-date with your MongoDb data.

Use Cases to transfer your MongoDb data to S3 Glue

Integrating data from MongoDb to S3 Glue provides several benefits. Here are a few use cases:

Advanced Analytics: S3 Glue’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.
Data Consolidation: If you're using multiple other sources along with MongoDb, syncing to S3 Glue 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.
Historical Data Analysis: MongoDb has limits on historical data. Syncing data to S3 Glue allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: S3 Glue provides robust data security features. Syncing MongoDb data to S3 Glue ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: S3 Glue can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding MongoDb data.
Data Science and Machine Learning: By having MongoDb data in S3 Glue, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While MongoDb provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to S3 Glue, providing more advanced business intelligence options. If you have a MongoDb table that needs to be converted to a S3 Glue table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a MongoDb account as an Airbyte data source connector.
Configure S3 Glue as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from MongoDb to S3 Glue 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!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

Easily address your data movement needs with Airbyte Cloud

Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team.

Get started with Airbyte for free

Talk to a data infrastructure expert

Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure.

Talk to sales

Improve your data infrastructure knowledge

Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.

Subscribe to newsletter

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Jean-Mathieu Saponaro

Data & Analytics Senior Eng Manager

"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"

Learn more

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Alexis Weill

Data Lead

“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria. The value of being able to scale and execute at a high level by maximizing resources is immense”

Learn more

How to Sync MongoDb to S3 Glue Manually

Step 1:

Step 2:

Step 3:

Step 4:

Step 5:

Step 6:

Step 7:

Step 8:

FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is MongoDb?

What data can you extract from MongoDb?

MongoDB gives access to a wide range of data types, including:

1. Documents: MongoDB stores data in the form of documents, which are similar to JSON objects. Each document contains a set of key-value pairs that represent the data.
2. Collections: A collection is a group of related documents that are stored together in MongoDB. Collections can be thought of as tables in a relational database.
3. Indexes: MongoDB supports various types of indexes, including single-field, compound, and geospatial indexes. Indexes are used to improve query performance.
4. GridFS: MongoDB's GridFS is a specification for storing and retrieving large files, such as images and videos, in MongoDB.
5. Aggregation: MongoDB's aggregation framework provides a way to perform complex data analysis operations, such as grouping, filtering, and sorting, on large datasets.
6. Transactions: MongoDB supports multi-document transactions, which allow multiple operations to be performed atomically.
7. Change streams: MongoDB's change streams provide a way to monitor changes to data in real-time, allowing applications to react to changes as they occur.

Overall, MongoDB provides access to a flexible and powerful data model that can handle a wide range of data types and use cases.

How do I transfer data from MongoDb?

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 to S3 Glue as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from MongoDB to S3 Glue and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials

Warehouses and Lakes

Databases

How to load data from MongoDb to S3 Glue

Learn how to use Airbyte to synchronize your MongoDb data into S3 Glue within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 1: Setup MongoDb

Step 2: Setup S3 Glue

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between MongoDb and S3 Glue

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up MongoDb as a source connector (using Auth, or usually an API key)
set up S3 Glue as a destination connector
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

What is S3 Glue

Integrate MongoDb with S3 Glue in minutes

Try for free now

Prerequisites

A MongoDb account to transfer your customer data automatically from.
A S3 Glue account.
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.

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.

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 S3 Glue as a destination connector

Step 3: Set up a connection to sync your MongoDb data to S3 Glue

Once you've successfully connected MongoDb as a data source and S3 Glue as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select MongoDb from the dropdown list of your configured sources.
Select your destination: Choose S3 Glue from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific MongoDb objects you want to import data from towards S3 Glue. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from MongoDb to S3 Glue according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your S3 Glue data warehouse is always up-to-date with your MongoDb data.

Use Cases to transfer your MongoDb data to S3 Glue

Integrating data from MongoDb to S3 Glue provides several benefits. Here are a few use cases:

Advanced Analytics: S3 Glue’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.
Data Consolidation: If you're using multiple other sources along with MongoDb, syncing to S3 Glue 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.
Historical Data Analysis: MongoDb has limits on historical data. Syncing data to S3 Glue allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: S3 Glue provides robust data security features. Syncing MongoDb data to S3 Glue ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: S3 Glue can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding MongoDb data.
Data Science and Machine Learning: By having MongoDb data in S3 Glue, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While MongoDb provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to S3 Glue, providing more advanced business intelligence options. If you have a MongoDb table that needs to be converted to a S3 Glue table, Airbyte can do that automatically.