7 Best NoSQL Databases Ranked by Popularity

Data drives business – there’s no doubt about that. Without data, every company on the planet would struggle to successfully bring products to market in this world of ever-increasing challenges. You see, part of the problem is that, with each passing day, there are more and more companies vying for consumers' attention.

You may have the best idea for a product, but if you don't have the data needed to help you market that product to the right audience, you will struggle to achieve your goals. This means you need to use a highly scalable database for your purposes.

But there are many types and options, from traditional relational databases (SQL databases) to NoSQL. It can be confusing to find a flexible data model that stores data, makes sense of the information, and facilitates the data retrieval process. Fortunately, you don't need to be certified in data science to solidify your practices.

We recommend finding a high-end NoSQL database.

While most traditional applications like WordPress run on SQL databases, many modern applications that work with large amounts of unstructured data rely on NoSQL databases. Without this type of database, your company would not be able to work with the information in a way that benefits your marketing, sales and management teams.

Think about it. In this modern era, you need to give your teams every advantage they can get because you can bet the competition will certainly do so. This means the right way to store data, maintain data integrity, and leverage it effectively for modern use cases.

What are NoSQL databases?

The 2 most used databases are SQL (relational databases) and NoSQL (non-relational databases). But what does it mean? And what is the difference between them?

The main distinction is that a NoSQL database works with a dynamic schema, which allows you to use unstructured data. This means you can build an application without having to build a database schema first.

When building an application with a relational database, you must know how the application will work with specific tables made up of rows and columns. Before adding this first piece of data to the database, the schema must be defined. Neglect this and your application will not be able to work with the database.

On the other hand, a NoSQL database does not require the use of structured data. With this type of database, data requirements can evolve as needed without causing problems for the database. In fact, a NoSQL database can work with and store data of all types, including:

• Video clips
• Mobile device activity
• Social media use
• Text documents
• Images

Many companies use NoSQL databases, such as:

• Amazon
• LinkedIn
• Google
• Facebook
• Adobe
• Capgemini
• SAP
• Qualcomm
• JP Morgan

If your company is thinking about adopting a NoSQL database or planning to build an application that relies on data, know that if you choose to go this route, you're in good company. Given that many Fortune 500 companies rely on NoSQL databases, this technology has proven to be the best option for applications and services at scale.

Compared to relational database, NoSQL database means you are not limited to just text-only inputs. And since these databases have become so crucial to businesses everywhere, you should have no trouble finding a strong NoSQL development company to hire.

What are the main benefits of NoSQL databases versus relational databases?

NoSQL offers many benefits over traditional SQL database such as:

• SQL databases are vertically scalable but have significant costs associated with scaling, while NoSQL databases can be scaled without incurring the same costs.
• NoSQL databases are considerably more reliable at scale.
• NoSQL databases are best suited for modern applications with complex and constantly changing datasets, especially at scale.
• NoSQL databases can store and process data in real time, so in addition to being more scalable, they also perform considerably better.

Switching from a SQL database to a NoSQL database is not as easy as, say, switching from one office suite to another. There are certain things you should consider when dealing with structured and unstructured data.

Things to Consider When Choosing a NoSQL Database

When making the switch, you should consider the following factors:

1. Cost: Does your company have the budget to train your staff in the use of databases, or can you hire the necessary staff?
2. ACID: Does your data require ACID properties? In this case, it is better to use existing SQL databases.
3. Scalability: Does your app need to scale at the level of, say, Facebook? In this case, NoSQL will be a requirement.
4. Savings: Will migrating to a NoSQL database save your company money? It’s not just about training, it’s also about deployment and management. Keep these costs in mind when considering the move.
5. Venture Capital Money: Are you creating a startup company that relies on venture capital? In this case, it's best to consider a NoSQL database because most Silicon Valley VCs won't think twice about a company using a SQL database. It's all a matter of perception.
6. High availability vs. reliability: Does your application require high availability rather than data reliability? In this case, choose a NoSQL database; otherwise, opt for SQL.

Now that you have an idea of ​​what NoSQL databases are for (and whether you should use them), let's take a look at some of the best versions available in 2023.

Top 7 NoSQL Databases Available in 2024

Anyone looking to adopt a NoSQL database for a scalable application should seriously consider any of the following options.

#1MongoDB

MongoDB is a scalable, object-oriented NoSQL database based on the NoSQL document storage model. This database stores objects as separate documents within a collection with JSON-like documents.

MongoDB was originally created by 10gen software in 2007 as a component for a platform as a service product. 10gen moved in 2009 to an open source database model, offering commercial support. In 2013, 10gen changed its name to MongoDB Inc. and retained the open source license.

MongoDB is now a publicly traded company, based in the United States and Ireland.

Main features

• Ad hoc queries: MongoDB enables optimized, real-time data analysis.
• Improved indexing : MongoDB indexing can accommodate real-time and changing query patterns.
• Better replication : MongoDB handles replication, so it's easier to achieve high availability.
• Sharding : MongoDB supports sharding so that larger data sets can be distributed across multiple distributed collections.
• Load Balancing : With the help of sharding and replication, MongoDB supports large-scale load balancing.

#2 Apache Cassandra

Apache Cassandra is an open source, distributed, wide column store NoSQL database management system. From the beginning, this database was designed to handle large amounts of data on off-the-shelf server clusters so that it is capable of scaling without the need to purchase specialized, expensive hardware.

Apache Cassandra was originally created by Avinash Lakshman and Prashant Malik to power Facebook's index search feature. In July 2008, Cassandra was released as an open source project on Google Code, and in March 2009 it became an Apache incubator project, only to become a top-level project on February 17, 2010.

Main features

• Distributed Database : Apache Cassandra is built to run multiple nodes of equal importance, meaning there is no “master” and no bottlenecks.
• Elastic scalability : Apache Cassandra can scale up and down with little resistance.
• Cassandra Query Language : Apache Cassandra uses its own query language which is similar to SQL query language.
• Fault Tolerant : Due to its data replication capability, Cassandra is inherently fault tolerant.

#3 Redis

Redis is another open source NoSQL database that works in memory. Redis can also be used as a cache and message broker, making it a bit more flexible than some other NoSQL databases.

Redis supports data structures such as strings, hashes, lists, sets, sorted sets with varying queries, bitmaps, hyperlogs, streams, and geospatial indexes with radius queries.

Redis was originally created by Salvatore Sanfilippo, who was trying to improve the scalability of his startup. The company's goal was to develop a real-time web log analyzer that traditional databases did not support. In 2009, Sanfilippo prototyped a proof-of-concept version of what would later become Redis. Very quickly, the project was noticed and soon adopted by companies like GitHub and Instagram.

Main features

• Performance: Redis data resides in memory, enabling very low latency and high throughput.
• Flexible data structures : Redis supports a large number of data structures, so you are not limited in the type of data used.
• Simplicity : Redis is considerably easier to use than other NoSQL databases.
• Replication and persistence : Redis supports replication and persistence for reliable data storage and retrieval.
• High availability and scalability : Since Redis is an in-memory database, it can achieve great scalability while providing reliable availability.

#4 Sofa

Sofa a NoSQL database originally called Membase, is an open-source, distributed, multi-model document database that has been optimized specifically for interactive applications.

Membase was created by several members of the Memcached project team after founding a company called NorthScale. NorthScale's goal was to develop a key-value store that offered the simplicity, speed, and scalability of Memcached and the storage, persistence, and query capabilities of a database.

Membase announced a merger with CouchOne (the company behind CouchDB) on February 8, 2011, which is where the name Couchbase comes from.

Main features

• SQL++ Engine: With this, Couchbase leverages SQL queries on JSON data.
• JSON data : This means it is flexible, readable, and easy to manage.
• Fast: Couchbase includes a built-in managed cache for speed.
• Scopes and Collections: Couchbase uses data organization similar to schemas and relational tables, so it should be immediately familiar.
• Cloud-friendly : Couchbase seamlessly adapts to cloud-native development and applications.

#5 Neo4j

As a highly scalable, native graph database, Neo4j is at the forefront of leveraging data relationships as first-class entities. Developed by Neo4j, Inc., this innovative technology emphasizes performance, reliability and flexibility, making it ideal for building sophisticated, intelligent applications that can seamlessly navigate, manage and leverage connected data structures.

Neo4j's graph model allows data to be stored in nodes and relationships, enabling fast traversal and complex queries that would be less efficient in traditional relational databases. By treating relationships as fundamental, Neo4j empowers developers to explore and exploit the intricate connections within their data, unlocking new insights and opportunities that were previously difficult to discover.

With its powerful, relationship-centric approach, Neo4j is revolutionizing the way we perceive and interact with data, paving the way for a new era of intelligent, connected applications across multiple domains.

Main features

• Graph-based model : Allows the storage of data in a graphical format, making it ideal for applications that rely heavily on relationships between data points.
• Cipher Query Language : Provides a powerful and intuitive query language tailored to access and manage graph data, simplifying complex data relationship queries.
• High performance : Optimized for connected data, enabling fast query performance even with deep relational queries.
• Scalability : Supports clustering for scalability and high availability, making it suitable for enterprise-grade applications.
• Rich Ecosystem : Comes with a variety of tools and libraries for development, including integrations with popular programming languages ​​and frameworks.

#6 Amazon DynamoDB

A fully managed, serverless key-value NoSQL database, Amazon DynamoDB delivers high performance at any scale. Part of AWS, it offers built-in security, automated backups and replication, in-memory caching, and data import/export tools. DynamoDB delivers seamless scalability and superior performance without operational overhead, enabling developers to innovate effortlessly.

Main features

• Fully managed : AWS takes care of provisioning, patching, and scaling, allowing developers to focus on application development.
• Performance at scale : Delivers single-digit millisecond performance at any scale, with the ability to handle more than 10 trillion requests per day.
• Serverless : There are no servers to manage or provision; it automatically scales up and down to adjust to various workloads.
• Global Tables : Provides fully replicated multi-region tables for building global applications.
• Integrated with AWS : Seamlessly integrates with other AWS services, making it an ideal choice for AWS-powered applications.

#7ArangoDB

Offering unparalleled versatility, ArangoDB is a next-generation multi-model NoSQL database that seamlessly supports graph, document, and key/value data models in a single engine. This unique flexibility allows developers to leverage the most appropriate data model for their applications without having to deal with multiple databases.

Designed for performance and scalability, ArangoDB excels at handling complex queries and transactions with ACID guarantees. Its query language, AQL, enables complex database operations on all supported data models, opening up new possibilities for data manipulation and analysis.

Main features

• Multimodel : Supports graphical, document, and key/value data models, enabling a wide range of applications.
• AQL : A powerful query language that supports CRUD operations, complex queries, and transactions across all data models.
• Scalability : Can be deployed as a single instance or in a distributed configuration, providing scalability and high availability.
• Graph capabilities : Offers advanced graphing capabilities, including graph analysis and traversal, making it ideal for applications that require complex relationship handling.
• Flexible deployment : Can be deployed on-premises, in the cloud, or in Kubernetes, offering flexibility in infrastructure options.

NoSQL: the bottom line

If your company is serious about developing applications that can achieve considerable scale, availability, and flexibility, you will need to employ a NoSQL database. Once you've decided which one to use, you'll want to ensure your teams follow NoSQL best practices to ensure the deployment, use, and management of your application is a success.