Hadoop or MongoDB: What is the Difference?
Hadoop and MongoDB are great solutions to work with big data. However, they each have their forces and weaknesses.
FAQs
When it comes to real-time data processing, MongoDB is much faster than Hadoop. The latter will work in batches and doesn’t optimize its memory management.
MongoDB is a general-purpose database that can also process big data. Its flexible schema enables it to accept any form or volume of data.
In many cases, MongoDB can replace Hadoop for storage of big data and data processing. However, there are use cases where you might still need Hadoop. In those cases, you can use Hadoop to complement MongoDB.
No. MongoDB and Hadoop are two separate products.
Hadoop is a collection of software used to store and process big data. It works well for unstructured data.
Hadoop and MongoDB both have specific use cases. However, in many scenarios, you can use MongoDB to replace Hadoop. For the occasional use cases where Hadoop is needed, you can use it with MongoDB. For this reason, MongoDB is more flexible than Hadoop.
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