Most things come better as a pair — chocolate and vanilla, gin and tonic, and Simon and Garfunkel. But three is not always a crowd. lets you integrate MongoDB and Apache Hadoop so you can run complex analytics for all the data you store in MongoDB with no code at all. Stress-free MongoDB Hadoop integration is now possible with — the latest powerful addition to your data stack.

 But why is MongoDB Hadoop integration so important? And why should you incorporate these tools into your data stack? In this guide, learn about connecting MongoDB with Hadoop — and using to do it for you. 

Table of Contents

  1. What is MongoDB Hadoop Integration?
  2. 3 Types of MongoDB Hadoop Integration
  3. MongoDB Hadoop Integration Benefits
  4. Problems With MongoDB Hadoop Integration
  5. MongoDB Hadoop Integration With
  6. Alternatives to MongoDB Hadoop Integration With
  7. Add to Your Data Stack

What is MongoDB Hadoop Integration?

MongoDB Hadoop integration lets you migrate MongoDB data into Hadoop so you can run powerful analytics on the data you store in MongoDB. 


MongoDB is a NoSQL database for operational storage of all kinds of big data — text files, customer records, images, videos, you name it. It stores data as semi-structured data in the JavaScript Object Notation (JSON) format.

MongoDB is an object-oriented, scalable, and open-source database, storing data objects as documents inside a collection instead of columns and rows (like a conventional relational database). Uber, Lyft, and Delivery Hero have already incorporated MongoDB into their data stacks. The platform lets these companies store valuable data about customers, drivers, and trips. 

For more information on's native MongoDB connector, visit our Integration page.


Apache Hadoop Distributed File System (HDFS), or Hadoop for short, is an open-source program designed for distributed batch processing of big data sets. Like MongoDB, Hadoop isn't a traditional relational database and leverages text files, customer records, images, videos, and other data. However, the platform doesn't store the data in the JSON format. Instead, it uses specific languages and libraries to interact with data such as: 

British Airways, Expedia, and Royal Bank of Scotland are among the many global companies that use Hadoop

Recommended Reading: What is Apache Hadoop?


MongoDB or Hadoop?

You don't have to choose between MongoDB and Hadoop because both platforms integrate. By combining these platforms, you can run data analytics and access intelligence about various components in your business, such as sales, engagement, and fraud prevention. 

3 Types of MongoDB Hadoop Integration

There are three ways to integrate MongoDB with Hadoop: 

  1. Gather data from MongoDB and compile the data in a simplified, summarized format inside Hadoop — a process called data aggregation.
  2. Move data from MongoDB to Hadoop, using Hadoop as a data warehouse for business insights. (Or run MongoDB data in Apache Hive.) 
  3. Extract data from MongoDB, transform the data into a usable format, and load it into Hadoop — a process called Extract, Transform, and Load (ETL).

In all these scenarios, you can still store data in MongoDB for operational queries. But Hadoop aggregates or compiles the data for analytics. (You can also use other business intelligence tools to generate further insights.) 

Tip: Hadoop handles semi-structured data like the JSON format, so migrating MongoDB data to Hadoop is simple.

MongoDB Hadoop Integration Benefits for Big Data

Creating a data stack — a list of all the platforms and technologies you require for data management and analytics — with MongoDB and Hadoop provides you with multiple benefits:

  • Combine the power of MongoDB and Hadoop
  • Simplify and summarize MongoDB data
  • Contextualize MongoDB data
  • Power big data applications by adding context to online applications
  • Improve latency query responsiveness
  • Prepare data for analytics 
  • Run analytics in Hadoop
  • Improve data quality 
  • Improve data compliance for GDPR, HIPAA, and other frameworks 

Some of the world's largest companies combine MongoDB and Hadoop, such as FourSquare and Orbitz. 

Problems With MongoDB Hadoop Integration

Combining MongoDB and Hadoop requires a lot of complicated code, which proves difficult if you lack a data engineering team. MongoDB Hadoop integration can also be expensive, requiring infrastructure and resources. 

Imagine if there were a way to migrate data from MongoDB to Hadoop without the use of code. With, it's now possible. 

MongoDB Hadoop Integration with makes Mongo-Hadoop integration much easier: 

  • offers Hadoop-as-a-service, which eliminates the need to invest in additional infrastructure or hardware to migrate data from MongoDB to Hadoop, potentially saving you thousands of dollars. Plus, you can scale your data in the cloud
  • requires no code whatsoever, making MongoDB and Hadoop migration simple. 
  • offers free support for all users. 
  • has a simple pricing structure based on the connectors you use, not the data you consume. So you pay the same amount month after month, with no hidden fees or nasty surprises. 
  • Optimize data management and analytics further with over 200 out-of-the-box transformations and connectors, including Salesforce-to-Salesforce capabilities.  

How Does Streamline MongoDB Hadoop Integration?

The web application lets you create Hadoop clusters quickly. Just set up data processing via's intuitive UI and run MapReduce tasks on Hadoop straight away. Everyone can integrate MongoDB with Hadoop, regardless of coding or data science experience., MongoDB, and Hadoop make the perfect data stack because: 

  • You can store JSON data in MongoDB.
  • You can use Hadoop to analyze and contextualize MongoDB data.
  • You can use to migrate MongoDB data to Hadoop with no code or additional infrastructure.

Tip: imports MongoDB data to Hadoop securely, adhering to all security protocols. Migrating MongoDB data in this way improves data compliance in your organization. 


How Does MongoDB Hadoop Integration Work With combines MongoDB and Hadoop via the ETL process. With, you can:

  1. Extract semi-structured data from MongoDB,
  2. Transform the data into a readable, usable format, and
  3. Load it into Hadoop.

Once you've moved data to Hadoop, you can run powerful analytical models that influence your decision-making processes. Many of the world's most successful companies migrate MongoDB data to Hadoop for: 

  • Customer segmentation
  • Risk modeling 
  • Increasing sales and revenue 
  • Predictive analytics 
  • Cost-cutting
  • Data storage
  • Identifying business-related problems
  • Improving customer engagement 
  • Data replication
  • Machine learning
  • Querying
  • Indexing
  • Scalability

You can also run analytics with third-party business intelligence tools or move data to another data warehouse such as Hive. (You'll still be able to add and edit data in MongoDB and Hadoop without affecting this process.)

Alternatives to MongoDB Hadoop Integration With lets you integrate the data you keep in MongoDB with other data sources and platforms for analytics and general data management. With, connect quickly to MongoDB data stores and benefit from a user-friendly point and click interface.

For example, you could create a MongoDB, Elasticsearch, and data stack, which moves MongoDB data to Elasticsearch via This process lets you search and analyze MongoDB data in real-time on Elasticsearch, helping you contextualize insights for various business-related purposes. Alternatively, create a MongoDB, MySQL, and data stack lets you create data pipelines between data sources, data warehouses, data lakes, and other data management solutions for more accurate real-time data analytics without knowing code like Java or Python. Typically, data engineers and coders need to facilitate these pipelines, but creates custom dataflows in a simple no-code graphical interface. Start from scratch or use one of the pre-made templates or a tutorial on the platform. 

Recommended Reading: Big Data Stack: Challenges and Solutions to Help You Unlock its Potential

Add to Your Data Stack


Creating a data stack with MongoDB, Hadoop, and provides your business with multiple benefits. Hadoop handles JSON data effectively, making it an excellent choice for MongoDB users that want to run analytical models. But integrating MongoDB and Hadoop is expensive and complicated, requiring lots of code and infrastructure., however, simplifies the process, helping you migrate data from MongoDB to Hadoop quickly with no code at all. 

But there's so much more to than just MongoDB Hadoop integration. This cost-effective ETL solution comes with over 200 out-of-the-box transformations and connectors that power your business, including Salesforce-to-Salesforce integration. You will also benefit from simple pricing and free support for all customers. 

Your MongoDB, Hadoop, and data stack could transform how you manage and analyze data within your organization. Schedule an intro call to try risk-free for 14 days.