Top 10 Open-Source NoSQL Databases in 2025

NoSQL databases are becoming more and more popular these days. This is because companies increasingly require NoSQL databases as traditional relational databases are not enough to fulfill their requirements anymore. Now companies have to deal with millions of users at the same time, handle insane quantities of both structured and unstructured data daily, and make sure there are no interruptions in their services. All these expectations have given rise to the NoSQL databases that are more agile, scalable, and also better suited to unprecedented levels of big data. That is why this article specifies the Top 10 Open-Source NoSQL Databases that you can use as per your specific requirements.

All these databases are open source and have free versions. These are miles ahead of relational databases in terms of speed, performance, and scalability, especially in regard to big data. However, it is also important to keep in mind that these databases are only required for superior needs, and many common applications can still be developed using relational databases. With that said, let’s check out these Open-Source NoSQL Databases and find out some of their specifications.

Top 10 Open-Source NoSQL Databases

Now lets explores the Top 10 Open-Source NoSQL Databases that you can leverage based on your specific requirements.

1. Apache Cassandra

Apache Cassandra is a free and open-source high-performance database that is provably fault-tolerant both on commodity hardware or cloud infrastructure. It can even handle failed node replacements without shutting down the systems and it can also replicate data automatically across multiple nodes. Moreover, Cassandra is a NoSQL database in which all the nods are peers without any master-slave architecture. This makes it extremely scalable and fault-tolerant and you can add new machines without any interruptions to already running applications. You can also choose between synchronous and asynchronous replication for each update.

2. Apache HBase

Apache HBase is an open-source distributed Hadoop database that can be used to read and write to big data. HBase has been constructed so that it can manage billions of rows and millions of columns using commodity hardware clusters. This database is based on the Big Table which was a distributed storage system created for structured data. Apache HBase has many different capabilities including scalability, automatic sharding of tables, consistent reading and writing capabilities, support against failure for all the servers, etc.

3. MongoDB

MongoDB is a general-purpose distributed database created for the application developers in this generation to use in the cloud. This is a document database that stores the data in JSON-like documents which is much more powerful and efficient than the traditional row and column databases. MongoDB also supports various methods of searching such as geographical searching, text searching, graph searching, etc. Another advantage of MongoDB is that it provides first-class security for its clients including SSL, firewalls, encryption, etc. And the best thing is you can also create visualizations using MongoDB data and connect with any Business Intelligence tools that are compatible with the MySQL protocol.  

4. Neo4j

Neo4j is a graph-based database that is excellent in handling not only data but also data relationships. Since Neo4j connects the data when it is stored in the database, it can access the data again much faster than conventional databases. Each data record has direct pointers to all the other data records it is connected with and this underlines the power of the database. Neo4j also uses Cypher queries that are much faster and simpler to write than SQL queries and since it doesn’t have any tables there is no need to bother about joins. Neo4j also provides drivers for  Java, .Net, JavaScript, Python and Go in an official capacity whereas the open-source community contributors provide many other drivers like Ruby, PHP,  R, C, C++, etc.

5. Apache CouchDB

Apache CouchDB is an open-source project and a single node database that allows you to easily store your data and access it when you need it. Couch DB can also scale up for more demanding projects into a cluster of nodes with multiple servers. It supports the HTTP protocol along with the JSON data format and also integrates with HTTP proxy servers. Apache CouchDB is designed for reliability with a crash-resistant structure that supports “Offline First” applications and a system that saves data redundantly so that it is never lost and available in a state of emergency.

6. OrientDB

OrientDB is an open-source NoSQL database that supports various models such as the graph, document, object key/value model, etc. It is written in Java. and the relationships between all the data records are managed using direct connections between them such as the case with graph databases. OrientDB also provides a strong emphasis on security and reliability. You can query the database and obtain data using a terminal console interface and also use a graph editor to visualize and interact with your data.

7. Riak

Riak is a distributed NoSQL database that is highly resilient and ensures data accuracy. It is created using multiple clusters that make sure data is not lost even in the event of a hardware failure and read/write operations can continue smoothly. Riak is designed using a key/value specification that solves many challenges in the management of big data such as tracking user data, copying the data in various locations all over the world, storing connected data, etc. Some of the features of Riak include scalability, operational simplicity, resiliency, complex query support, etc. It can also integrate with Apache Spark to provide real-time analysis of Spark.

8. Redis

Redis is an open-source database that supports many different data structures such as strings, lists, hashes, sets, sorted sets, etc. It is written in ANSI C and it can be used with almost all the programming languages and Linux and OS X operating systems. Redis works with an in-memory dataset to preserve its extremely fast performance and the implementation uses the fork system call to create a duplicate of the current process with the data so that the parent process can continue its operations with the existing clients and the child process can create a data copy on the disk.

9. RavenDB

RavenDB is a NoSQL document database that provides the benefits of a NoSQL database with all the conveniences of a relational database. It also offers fully transactional (ACID) data integrity so you can use it along with your existing SQL databases to get the most out of both types. This database is also highly scalable and it can create new nodes to keep up with increasing data traffic. RavenDB is available for installation on-premises as well as in the form of a cloud service provided by Amazon Web Services, Azure, etc.

10. Hypertable

Hypertable is NoSQL open-source database that was designed to combat the scalability problem that appears in all relational databases. It was based on the Google Big Table design and written in C++. Hypertable runs in both Linux and Mac OS X. It is also suitable for a wide range of applications as it keeps the data sorting using a primary key, unlike most other NoSQL databases that use the hash table design. Hypertable is also suited to provide maximum efficiency with minimum performance and stability costs which makes it extremely cost-efficient.

Must Read:

• Top 5 Reasons to Choose NoSQL
• SQL vs NoSQL: Which one is better to use?
• Top NoSQL databases Every Data Scientist Should Know About

Conclusion

All of these Open-Source NoSQL Databases are quite popular and frequently used by many companies as per their needs. Among these, Apache Cassandra and MongoDB are arguably the most famous with 40% of the Fortune Hundred Companies using Cassandra. However, you can select any of these databases for usage as per your requirements as each of them has its benefits and individual functionalities.