With organizations generating huge volumes of Unstructured Data, the need for NoSQL Databases is on the rise. Relational Databases organize data into tables or relations, which are intersections of rows and columns. This makes them limited to storing Structured Data only. NoSQL databases emerged in 2009 to overcome this limitation. They can be used in massive data applications to store Unstructured Data. 

MongoDB is a popular NoSQL database management system. It is an open-source NoSQL database that uses the document-oriented database model. MongoDB groups data into documents and collections rather than tables, hence, it can be used to store different types of data. It is well-known for offering high performance, easy scalability, and high availability. 

However, data consumption in MongoDB is high as a result of denormalization. Developers have also reported different issues with MongoDB, hence, they are leaving the Database Management System. In this article, we have prepared a list of the top MongoDB Alternatives for you to use.

Table of Contents

What is MongoDB?

MongoDB is a well-known Open-Source NoSQL Database written in C++. MongoDB is a Document-oriented Database that uses JSON-like documents with a Dynamic Schema to store data. It means that you can store your records without having to worry about the Data Structure, the number of fields or the types of fields used to store values. Documents in MongoDB are similar to JSON objects.

You can change the structure of records (which MongoDB refers to as Documents) by simply adding new fields or deleting existing ones. This feature of MongoDB allows you to easily represent Hierarchical Relationships, Store Arrays, and other complex Data Structures. Nowadays, many tech giants, including Facebook, eBay, Adobe, and Google, use MongoDB to store their large amounts of data.

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  • Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
  • Schema Management: Hevo can automatically detect the schema of the incoming data and maps it to the destination schema.
  • Connectors: Hevo supports 150+ Integrations to SaaS platforms FTP/SFTP, Files, Databases, BI tools, and Native REST API & Webhooks Connectors. It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake, Firebolt, Data Warehouses; Amazon S3 Data Lakes; Databricks; and MySQL, SQL Server, TokuDB, MongoDB, PostgreSQL Databases to name a few.  
  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
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Best MongoDB Alternatives

The following are the top MongoDB Alternatives that you should consider:

1. Apache Cassandra

MongoDB Alternatives: Apache Cassandra
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If you are looking for a Database Management System that offers high availability and scalability without affecting performance, consider Apache Cassandra is one of the best MongoDB alternatives to consider.  It is an Open-Source NoSQL database that enables operational simplicity and support replication across many data centers and cloud availability zones. When data is replicated in multiple nodes, it ensures that the system is fault-tolerant. Cassandra was initially developed for Facebook but you can deploy it across multiple servers very quickly. Every node in the cluster works separately, thus, you don’t have to worry about bottlenecks in the system. 

However, some Apache Cassandra users have reported that it doesn’t offer consistently high availability and its performance can be unpredictable. It has a free version and they can customize the costs according to your needs.

2. Redis

Redis
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This is an Open-Source Database and one of the MongoDB alternatives. It uses Active-Active and Active-Passive distributed architectures for high availability. Just like Apache Cassandra, Redis comes with powerful built-in search capabilities and a linearly scaling high performance. Redis is a fast Database Management System that supports different data structures including Hashes, Bitmaps, Lists, Sets, Strings, and others. 

Redis is a good NoSQL Database Management System for developers who are looking for speed. Its pricing starts at $5 monthly (100MB and four datasets) and it offers a 30MB free tier

3. DynamoDB

DynamoDB
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DynamoDB is a nonrelational Database Management System from Amazon. It groups data into key-value pairs and helps businesses to achieve a single-digit millisecond performance even on large-scale data operations. 

It is a multi-master, fully managed, and multi-region database that offers in-memory caching, security, and built-in backup and restore which makes it one of the best MongoDB alternatives. The good thing about DynamoDB is that it is capable of handling up to 10 trillion requests per day and supports peaks of over 20 million requests per second. DynamoDB can be expensive but it is worth the money to those running global-scale applications. Amazon DynamoDB has a free version and a free trial. It uses an on-demand pricing model. 

4. OrientDB

OrientDB
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OrientDB is an Open-source, NoSQL Database and one of the best MongoDB alternatives. If you are looking for a graph database, OrientDB may be the best option for you. Once you master its True Graph Engine, you won’t need to handle other data types or implement many systems. OrientDB is also an excellent database management system for modeling data with many complex relationships, and unlike other MongoDB alternatives, it offers free clustering. 

However, OrientDB users have complained of compatibility issues, poor documentation, and the high cost of hosting. OrientDB is one of the best MongoDB alternatives to those in need of the true power of graph databases. It has a free community edition and its price starts at $5,970

5. CouchDB

CouchDB
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CouchDB is an Open-source NoSQL Database written in the Erlang programming language. It is a document-oriented database that can be deployed as a standalone application framework or with high-volume distributed applications, particularly web applications capable of handling huge volumes of loosely structured data. CouchDB used the JSON format to store data, and it relies on sessions and authentication for durability and security. However, CouchDB users have complained of an unfriendly user interface and lack of full-stack search. 

CouchDB is one of the best MongoDB alternatives if you want to handle massive volumes of loosely structured data. It is free. 

6. ArangoDB

ArangoDB
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ArangoDB is a NoSQL Database Management System and one of the graph databases that can be used as MongoDB alternatives. It is used to ensure high availability of high-performance applications. It comes with a SQL-like query language and a flexible data model for key values, graphs, and documents. 

ArangoDB is also supported by a large community of users and it has a built-in search engine and a microservices framework. When using ArangoDB, you can run graph analytic queries and reduce the number of database technologies used in the production environment. It is one of the best MongoDb alternatives that can help you to build high-performance applications. 

ArangoDB has a free version and the cost of its enterprise edition can be customized to meet your specific needs. 

7. RethinkDB

RethinkDB
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This is an Open-Source Database Management System built for the storage of JSON documents. It is an ideal database for use in multiregional, multi-datacenter environments since you can scale to multiple machines without much effort.  RethinkDB can prove to be one of the best MongoDB alternatives for you if your goal is to develop real-time apps. However, you will not receive regular updates as the company was shut down in 2016. RethinkDB is a free and open-source database management system. 

Those are some of the best MongoDB Alternatives. 

Conclusion

This is what you’ve learned in this article:

  • NoSQL Databases are good for the storage of Unstructured Data as they don’t organize data into relations, which are intersections between rows and columns. 
  • MongoDB is a popular NoSQL Database. It uses the document-oriented database model and groups data into documents and collections. 
  • However, MongoDB users experience high data consumption because of denormalization. That’s why it’s good to know the best MongoDB alternatives. 
  • Some of the best MongoDB alternatives include Redis, Apache Cassandra, RethinkDB, DynamoDB, OrientDB, CouchDB, and ArangoDB. 

As your business begins to grow, data is generated at an exponential rate across all of your company’s SaaS applications, Databases, and other sources. To meet this growing storage and computing needs of data,  you would require to invest a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally load it to a Cloud Data Warehouse for further Business Analytics. All of these challenges can be efficiently handled by a Cloud-Based ETL tool such as Hevo Data.

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Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources like MongoDB and a wide variety of Desired Destinations, with a few clicks. Hevo Data with its strong integration with 150+ Data Sources (including 40+ free sources) allows you to not only export data from your desired data sources & load it to the destination of your choice, but also transform & enrich your data to make it analysis-ready so that you can focus on your key business needs and perform insightful analysis using BI tools.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable Hevo Pricing that will help you choose the right plan for your business needs.

Share with us your experience of learning about the best MongoDB Alternatives in the comments below!

Nicholas Samuel
Freelance Technical Content Writer, Hevo Data

Skilled in freelance writing within the data industry, Nicholas is passionate about unraveling the complexities of data integration and data analysis through informative content for those delving deeper into these subjects. He has written more than 150+ blogs on databases, processes, and tutorials that help data practitioners solve their day-to-day problems.

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