MongoDB VS Elasticsearch

MongoDB vs Elasticsearch | Full comparison in 2022

With each passing day, the popularity of the NoSQL databases is skyrocketing. There any numerous No-SQL databases which will solve different customer use cases. In this blog, I will be comparing the two most popular NO-SQL databases, MongoDB vs Elasticsearch.

What is MongoDB

what is MongoDB

Mongodb is one of the most popular open-source, No-SQL databases.MongoDB is non-relational and can have a dynamic schema that enables users to insert the data into MongoDB without defining the schema.

In MongoDB, users have the flexibility to define the schema to force users to insert data having particular fields. It can handle operational, transactional, and analytical workloads easily.

MongoDB uses the BSON format to represent the data and is easily scalable as per one’s requirements. You can interact with MongoDB either by command line or using an atlas.

You can follow the below links to get a basic understanding of MongoDB

Mongodb basic command

MongoDB create database

MongoDB create collection

MongoDB connection string

What is Elasticsearch

What is Elasticsearch

Ealstcisearch is an open-source, NO-SQL database. Elasticsearch is built on top of Apache Lucene and written in JAVA.

Elasticsearch allows you to search, store, and analyze vast volumes of data quickly and in near real time. It gives output in milliseconds because instead of searching for text,elasticsearch searches for an index.

Many well-known companies useElasticsearch, such as – Accenture, Linkedin, OpenStack, etc. Elasticsearch is usually used along with Kibana and Logstash to form the ELK stack.

Features of MongoDB vs Elasticsearch

Features of MongoDB vs Elasticsearch

Please follow this link to learn about the features of mongodb.

The Important features ofElasticsearch are as follows:

  • Scalable: Elasticsearch can be easily scalable as per user need. It can scale to handle petabytes of data.
  • Open source: Elasticsearch is completely open-source and free to download.
  • Improved search performance: Elasticsearch uses denormalization to improve query search performance.

Advantage of MongoDB vs Elasticsearch

Advantage of MongoDB vs Elasticsearch

Please follow this link to learn about the Advantage of Mongodb.

The Advantages ofElasticsearch are as follows:

  • Elasticsearch is developed on Java, which is one of the most popular languages.
  • Elasticsearch saves the data in JSON documents.
  • Elasticsearch is pretty fast when it comes to performance.
  • It replicates the data into multiple servers, leading to high availability.
  • Elasticsearch supports a wide variety of document data types.

Disadvantage of MongoDB vs Elasticsearch

Disadvantage of MongoDB vs Elasticsearch

Please follow this link to learn about the disadvantage of Mongodb.

The Disadvantages ofElasticsearch are as follows:

  • Elasticsearch does not support ACID-compliant out of box
  • It has been so many issues with Garbage Collection (GC)
  • Elasticsearch Should not be used as a primary persistence store.
  • Elasticsearch has a problem with Auto sharding
  • Elasticsearch required a steep learning curve

MongoDB vs Elasticsearch

Mongodb vs elasticsearch

In this session, we will make a detailed comparison of MongoDB vsElasticsearch.

MongoDB vs Elasticsearch General Difference

MongoDB is a NO-SQL databaseElasticsearch is also a NO-SQL database
MongoDB is written in C++Elasticsearch is written in JAVA
MongoDB can be installed on mac, windows, Linux, and UNIX systemsElasticsearch can be installed on mac, windows, Linux, and UNIX systems
MongoDB is primarily used as a document storeElasticsearch is primarily used as a search engine
MongoDB was developed in the year 2009 by MongoDB, IncElasticsearch was developed in the year 2010 by Elastic
Open source and free to downloadOpen source and free to download
Schema freeSchema free
supports Shardingsupports Sharding
No support for Foreign keysNo support for Foreign keys
support data replicationsupport data replication
MongoDB supports BSON data format, which is similar to JSONElasticsearch supports the BSON data format

MongoDB vs Elasticsearch Write Performance

MongoDB outperformedElasticsearch on many occasions. Mongodb functions exceptionally well with fewer indexes, whereas to get the same performance fromElasticsearch, we need to have moreindexes. Mongodb outperformedElasticsearch with queries on similar indexing.

MongoDB vs Elasticsearch pricing

Mongodb is budget-friendly when comparing MongoDB withElasticsearch as MongoDB provides more features like LDAP integration, backup, and atlas at less cost.

Also, Mongodb required fewer Indexes than ElasticSearch to give the same performance. So if cost is your primary concern, then choose mongodb over ElasticSearch.

Elasticsearch supports full-text search by default, and it provides many advanced features to support full-text search like tokenizers, token filters, analyzers, etc.

On the other hand, mongodb does not provide full-text search at speed and lacks advanced full-text search features like tokenizing text.

MongoDB vs Elasticsearch popularity

Elasticsearch has the number one rank in search engines and the eighth overall rank.

On the other hand, MongoDB takes the number one spot in document store databases and fifth overall rank.

MongoDB vs Elasticsearch Programming Language Support

Elasticsearch is written in Java and supports a wide variety of languages like JAVA,Python,Ruby,.NET, PHP, Rust, Perl, Javascript, GO, etc.

On the other hand, MongoDB is written in C++. Mongodb provides multiple drivers using which users can interact with Mongodb. Mongodb has drivers for most of the programming languages like:-C, C++, C#, GO, Java, Node.js, PHP, Python, Ruby, etc.

You can check my blog on MongoDB with python to understand how a user can interact with MongoDB using python.

MongoDB vs Elasticsearch Document Size

In Mongodb, a document of up to 16MB in size can be added. If you wish to save a large document, then you can save them using GridFS functionality.

On the other hand, The maximum document size that Elasticsearch supports goes up to 100 MB. However, it’s essential to remember that huge documents often create additional issues.

MongoDB vs Elasticsearch: which one to choose


This session will understand when to choose MongoDB over elasticsearch and vice versa.

  • When selecting any database, the first thing to keep in mind is how much data you are going to handle and how the data will grow in the near future.
  • Choose MongoDB over elasticsearch cost in your primary concern
  • Mongodb is more user-friendly and requires less attention from the user as compared toelasticsearch. so choose MongoDB when usability is your primary concern
  • Elasticsearch supports full-text search,and it provides many advanced features to support full-text search, whereas MongoDB has limitedfull-text search. so chooseElasticsearch when you need to perform frequentlyfull-text searches
  • Choose Elasticsearch you primarily need a search engine
  • Choose MongoDB when you need a database to store documents.


This article has started with a brief introduction to MongoDB and Elasticsearch. We also explored the advantages, disadvantages, and features of MongoDB vs elasticsearch. Finally, we have seen the difference between MongoDB vs elasticsearch and when to choose one over another.

I hope you like this tutorial. Please let me know in the comment box if you face any difficulty.

More to Read?

Mongodb vs Cassandra

Mongodb vs SQL

Mongodb vs Redis

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