Elasticsearch vs MongoDB

There are various databases to store data, such as Elasticsearch, Oracle, Postgres, MongoDB, and MySQL, etc. Elasticsearch and MongoDB are popular document-oriented database. Both are distributed and highly scalable datastores. Both databases offer backup and recovery facilities. Along with some common features, they also have some differences that make them different from each other. Therefore, it is very important to understand the difference between them.

What is Elasticsearch?

Elasticsearch is a NoSQL database that is used to store data in document form. It is an open-source search engine. Many well-known companies, such as - Accenture, Linkedin, and OpenStack, use Elasticsearch. It is developed in Java and top of the Apache Lucene. Elasticsearch is a real-time analysis engine designed for storing logs. Elasticsearch is a best choice in case when an application that requires too many filters or search operations.

What is MongoDB?

MongoDB is document-oriented NoSQL database. It works on the concept of document and collection. It is a schema-less database that is written in C++. MongoDB supports dynamic query on documents. As MongoDB is a NoSQL data, it uses dynamic schema for documents. MongoDB is able to handle the JSON document and allows the binary conversion of the JSON document. It can convert the JSON into BSON (Binary version of JSON). BSON is nothing but a binary version of JSON, which is similar to it.

Difference between Elasticsearch and MongoDB

There are some differences between Elasticsearch and MongoDB are listed below: