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9 Best MongoDB Alternatives In 2023

MongoDB Alternatives

The top 9 MongoDB substitutes (both free and paid) for 2023. An open source NoSQL DBMS called MongoDB has a document-oriented database approach. It supports a variety of data formats. However, MongoDB’s de-normalization causes a high data consumption rate.

9 Best MongoDB Alternatives In 2023

In this article, you can know about out 9 Best MongoDB Alternatives In 2023 here are the details below;

So, below is a carefully compiled checklist of the Top 9 MongoDB substitutes. This list includes software that is both open-source and commercial with the most recent download link and popular features.

1. RethinkDB

The scalable, open-source DBMS is called RethinkDB. It makes creating real-time apps significantly simpler for you. This DBMS solution is simple to set up, has intuitive operations, a rich query language, and monitoring APIs. Also check PSD2


This MongoDB substitute makes it far simpler to create and scale real-time applications.

You can create contemporary apps using your preferred web framework.

Real-time technologies like SignalR and can also be paired with you.

Enables you to incorporate the newest database technology advancements

Create location-aware apps and use joins to express relationships

2. OrientDB

An open source NoSQL multi-model database is OrientDB. It enables businesses to fully utilize graph databases without having to set up additional systems to handle different sorts of data. This open source MongoDB substitute aids in scalability, speed, and security improvements.


For faster deployment, it is concentrated on Scalability and High Performance Unified Multi-Model API.

TinkerPop3 for the current state of the efficient enhancements

Improved query planner and execution

3. CouchDB

An open source NoSQL database called CouchDB is built on the industry standard to provide web accessibility across a wide range of devices. In CouchDB, data is arranged as key-value pairs and saved in the JSON format.


It enables you to host a single logical database server on as many physical or virtual servers as you choose.

Additionally, the CouchDB utility performs best when used alongside external tools like HTTP proxy servers and load balancers.

Support for Authentication and Sessions

Using a multi-node CouchDB cluster, you can store data twice.

4. Arangodb

A native multi-model DBMS system is ArangoDB. With a single database core and a common query language (AQL), it supports three different data models. Declarative query language allows you to compare several data access strategies with just one query.


The key/value, document, and graph models are all supported by this tool, which was created as a native multi-model database.

For any data model, it can function as a highly scalable database cluster.

You can replicate a distributed database running in one datacenter to another datacenter.

Protect your data with top-notch high-security features.

5. PostgreSQL

A widely used open source database management system is PostgreSQL. One of MongoDB’s top rivals, it offers support for both SQL and JSON for relational and non-relational queries.


Concurrency control with several versions is supported.

Support for client-server network architecture provides high availability and standby servers

Compatible with ANSI-SQL2008 and object-oriented

6. Apache Cassandra

You should choose Apache Cassandra if you want high availability and scalability without sacrificing performance. This MongoDB substitute utility offers assistance with replication across different datacenters. Also check New Technology Trends 


To create a system with fault tolerance, data is replicated across many nodes.

Considering that every node in the cluster is sperate, there are no network bottlenecks.

Cassandra provides assistance with contracts and outside services.

Aids in deciding whether to utilize synchronous or asynchronous replication for each update.

7. IBM Cloudant

A distributed DBMS system with full management is called IBM Cloudant. One of the greatest alternatives to MongoDB, it enables you to store online and mobile applications while maintaining extreme scale data access and availability.


Clusters spanning all zones are used to deploy all instances.

Readable and writeable copies of the data are replicated across various data centers in synchronized fashion.

The built-in key value, MapReduce, full-text search, and geospatial querying features help improve your apps.

Aids in utilizing a robust API with a configurable JSON syntax that is compatible with Apache CouchDB

8. DynamoDB

A non-relational database is called Amazon DynamoDB. This database system includes in-memory caching, built-in security, and consistent latency. A serverless database called DynamoDB automatically scales and backs up your data for security.


Amazon is supported by key-value and document data models. For your DynamoDB, DynamoDB Accelerator provides quick read performance.

AWS Lambda and DynamoDB work together to provide triggers.

Secondary indexes provided by DynamoDB allow for flexible querying on any attribute.

The following URL is a download link for Dynamodb:

9. CockroachDB

A distributed, open-source SQL database called CockroachDB was created by Cockroach Labs. It is an open source undertaking that took Google Spanner as its cue.


ACID-based, distributed, and scalable SQL system

As you scale business-critical apps, make sure they’re reliable and accurate.

Supports the deployment of containers

Deployments across many regions and data centers


Describe MongoDB.

An open-source NoSQL DBMS called MongoDB employs a document-oriented database approach. It supports a variety of data formats. MongoDB uses collections and documents rather than the tables and rows seen in conventional relational databases. The fundamental unit of data in MongoDB is a pair of key-value pairs, which make up documents.

Why MongoDB Should Never Be Used?

Due to de-normalization, MongoDB needs a lot of data. Furthermore, MongoDB has a rigid structure with drawbacks that are challenging to resolve, including difficult scaling, lack of support for transactions, excessive memory utilization, and poor speed.

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