Mongo DB and Hadoop Big Data: The Power of Two | Concetto Labs

Mongo Db And Hadoop: The Power Of Two

Author image By Manish Patel  |  Friday, July 14, 2017 11:45 AM  |  3 min read  |   872

Hadoop and MongoDB


Mongo DB classified as under NoSQL database refers to an open-source cross-platform document database. It makes the integration of data easier and faster. This free software is used for backend by several multinational giants like eBay, New York Times, Viacom, and many more. It is one of the most famous NoSQL database systems.


Hadoop is the name given to the software technology created for storage and processing a plethora of data spread across commodity servers and commodity storage. Often Hadoop is considered to be the synonym of Enterprise Data Warehouse because of its growing application across industries to handle a large volume of data.


THE POWER OF TWO: Hadoop and Mongo DB

When the power of Hadoop and MongoDB is clubbed it results in the big data application success.

  • Hadoop creates the analytics model for the operational process and Mongo DB fuels the online and real-time operational applications targeting business processes and end-users.
  • Data is consumed by Hadoop from Mongo DB, to blend it with data received from different sources to come up with machine learning models and sophisticated analytics. The achieved results are directed back to MongoDB.
  • Here are a few examples of the combined usage of two by the corporate:
  • Mongo DB and Hadoop work together to create the base to bring into action the big data, to improvise the customer service, support up-sell and cross-sell or reduce the level of risk which otherwise hampers the efficiency of the business.
  • Here is a diagrammatic representation of MongoDB integration with Data Lake.


The sole purpose of MongoDB Connector for Hadoop is to ensure a high level of flexibility and a good level of performance and finally ease the integration of MongoDB with Hadoop ecosystem and Pig, Spark, Map Reduce, Hadoop Streaming, Hive plus Flume.


  • Creation of data splits to read from replica set configuration, standalone configuration, or shared configuration.
  • Use of MongoDB query language to filter the queries from source data.
  • Hadoop streaming support, to provide the freedom of writing in any language like python, ruby, etc.
  • Data from Mongo DB backup files can be read.
  • Data can be written in .bson format and be later imported to Mongo DB database with the assistance of Mongorestore
  • Mongo DB connector for Hadoop works with Mongo DB or BSON documents.


It can be downloaded through Maven or Gradle



  • To use Hadoop connector one needs compatibility with the following versions:
  1. Hadoop 1.X: 1.2
  2. Hadoop 2.X: 2.4
  3. Hive: 1.1
  4. Pig: 0.11
  5. Spark: 1.4
  6. MongoDB: 2.2


  1. Obtain Hadoop connector
  2. Obtain the JAR for MongoDB Java Driver
  3. Move each JAR to each of the Hadoop clusters. Make use of Hadoop Distribute Cache to direct the JARS to predefined nodes.

Concetto Labs can help create MONGO DB AND HADOOP Development


Concetto Labs is the reputed MongoDB and Hadoop big data development company India. They can assist you to explore more about this mobile application development platform and related technology.


Concetto Labs is the reputed
MongoDB and Hadoop big data development company



Author image

Manish Patel

Manish Patel is a Co-Founder of Concetto Labs, a leading mobile app development company specialized in android and iOS app development. We provide a one-stop solution for all IT related services.

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