Big data solutions and database services are innovative methods to manage the heaps of organized and unstructured data collected worldwide. MongoDB is a big data favorite.
MongoDB is a prominent open-source document-oriented database. MongoDB, a non-relational and NoSQL database program released in 2009, is used for big data applications. Collections and documents replace tables and rows.
It’s written in C++ and excellent for mobile apps, real-time analytics, IoT, etc. MongoDB is one of the most sought-after database talents among developers in 2022.
MongoDB’s primary characteristics include adequate data storage, ad-hoc queries for optimal and real-time analytics, a high insert rate for large write loads, proper indexing for good query executions, replication for enhanced data accessibility and stability, sharding, and load balancing.
NoSQL has the best database functionality, yet there are gaps. Even with its notable features and increasing community, it has flaws: excessive data consumption due to denormalization, absence of logic-binding methods, not being ACID-compliant, etc. Thus, developers are looking for alternatives.
This page lists MongoDB alternatives and competitors that may meet your needs.
Best MongoDB Alternatives
You can store JSON-like text with an optional schema (similar to MongoDB) in DynamoDB and Amazon Web Services (AWS) products. Among the best MongoDB alternatives, DynamoDB allows you to store data with an arbitrary schema.
Regarding security and performance, DynamoDB is a step ahead of MongoDB with the addition of “encryption at rest.” However, because they both use the same NoSQL format, the migration from MongoDB is simple.
Load balancing and automated sharding are already incorporated into DynamoDB. Programs can now store increasingly large amounts of data transparently.
PostgreSQL (commonly known as Postgres) is one of the most popular open-source databases. An emphasis is placed on scalability and SQL compliance.
Over the past two decades, it has gained much traction because of its extensive experience. SQL and JSON for non-relational queries, as well as MVCC and SQL, are all supported. Adding custom functions for languages like Java, C++, and others is a cinch.
With PostgreSQL, standby servers can be accessed at the highest level of performance. It is well-known for its speed and its ability to run smoothly across a wide range of platforms. Because it is compliant with ANSI-SQL2008, it performs admirably with both structured and unstructured data types.
If you’re a web developer concerned with performance, Redis might be your best bet. Because it uses an in-memory database, users may perform atomic transactions on data structures, including bitmaps, hashes, strings, lists, sorted sets and geospatial indexing with radius searches.
When it comes to working with large datasets, Redis performs well. In the case of prototype design, this could provide a challenge.
But this can be a plus if you have a well-structured plan in place, such as pre-existing services.
Any application that requires data to be transmitted across multiple servers, activities, and other services may benefit from the flexible data storage Redis.
Open-source database management system RethinkDB makes building modern and real-time programs easy with minimal effort. The setup is simple and the features are expandable and adaptable.
Development teams love its simple yet powerful query language, easily integrated with other technologies and the most recent database changes.
With the assistance of joins, it demonstrates relationships and performs API monitoring and interactive activities. An easy-to-use Docker file is included to run on Google Cloud, AWS and other platforms. Through change listeners, developers may monitor changes and respond to them.
5. Apache Cassandra
This application is written in Java on Linux, BSD, Windows, and OS X. Cassandra is adaptable and scalable, a non-relational open-source database that was initially developed by Facebook but is now the property of the Apache Software Foundation.
There are many advantages to using Cassandra, like being always available, having linear scale output, being operationally simple, and being easy to distribute over many data centers and cloud availability areas.
Compared to other Mongodb competitors, Cassandra provides better real-time insight than any other database management system. A look at Cassandra as a possible data storage solution for applications that need to manage big amounts of data might be beneficial.
If you’re looking for MongoDB alternatives, having a wide range of options gives you more leeway in making a decision. Your platform, requirements, and use case should all be considered before deciding.
In contrast, my personal favorites are Postgresql and DynamoDB. Redis and Cassandra are better suited for specific workloads than DynamoDB, which is the most popular option for people now using AWS infrastructure.