Databases have traditionally been known as proprietary tools offered by Microsoft, IBM, Oracle, and various smaller companies. However, things changed after the advent of popular open-source projects. New open source databases started emerging and taking over proprietary databases.
Today both open source and proprietary databases and database management tools have equal importance. I have already listed the comparison between commercial and open source databases here.
Especially, open source databases have gained much more importance and maturity – especially when it comes to new projects. Basically, the source code of open source software is freely accessible to everyone; as a result, anyone can distribute and modify it at their will.
It has been noted that open source database software tends to frequently include both database software and the database management tools needed to support the database.
In this article, I will help you understand the importance of an open source database and provide a list of the top ten and best open source database software available in 2023.
What are the features and benefits of using open source database software?
In the early days, open source software was met with skepticism by business professionals and entrepreneurs. However, those times are long behind us now. In a world dominated for a long by database suits like SQL Server and Oracle, open source databases have served as a refreshing and innovative solution allowing developers to create something that they can be truly proud of.
More and more companies have been adopting open source databases for massive enterprise projects.
As a result, more and more skilled Database Administrators are getting equipped with deep knowledge of these platforms for assisting with sensitive deployments. Apart from helping you with financial savings, open source databases have largely caught up (some even exceeded the competition) with their proprietary counterparts as far as features are concerned.
Extensive customization and community development are virtues of the open source model, which make it much more flexible than proprietary database software. Moreover, user communities tend to provide training materials free of cost as well. Here are some of the common features offered by open source database software:
- Data collaboration
- Data security
- Relational as well as non-relational databases
- Support for databases and database management
- Support for multiple platforms
Let us now go through a list of my choices for the top ten open source database software in 2022.
Top 10 Open Source Database Software
Every open source database software mentioned in this list is known not just due to its features but also due to its community support and exceptionally great reviews.
|Database Software||Type||Notable Features||Pros||Cons|
|MySQL||Relational||Easy to manage and configure; Integrates with development tools; Enterprise-level features||High-performance; widely supported; integrates well with various development tools||Requires high memory; Difficult to debug; Expensive for small businesses; Reported stability issues|
|Couchbase||Non-Relational||Enterprise-class cloud database; Combines NoSQL with SQL; Fast response time||Extremely fast; Complete control over data security; Good for business-critical applications||Slow backup and restore facilities; Documentation lacks real-life examples|
|Redis||Non-Relational (In-memory)||Data structure server; Pub-sub system; Supports various data structures||Fast reads and writes due to RAM-based nature; Easy to learn; No maintenance operations required||Lacks administration and monitoring tools; Encoding issues with CLI app|
|MongoDB||Non-Relational (Document-oriented)||Stores data as JSON-like documents with dynamic schemas; Good for indexing and querying||Integration of data in applications faster and easier; Excellent tool support||Query becomes complicated for data with relations; Slower join collections|
|PostgreSQL||Relational||Supports numerous workloads; Compatible with SQL; Compatible with various languages and tools||High performance; Reliable; Lower cost of ownership than MS SQL Server and Oracle||Room for improvement in support for JSON type and “full vacuum schema”; Installation process not uniform across all OS|
|Apache Hive||Non-Relational||Data warehousing; Querying and analysis of large datasets; Connectors for cloud platforms||Cost-effective for data warehousing; ETL, reporting, and analytics features||Not suitable for online analytical transaction processing; Complex joins take a long time to execute|
|MariaDB||Relational||Supports ACID-style data processing; Parallel data replication; JSON APIs||Developed by original developers of MySQL; Compatible features with Oracle Database; Advanced clustering||Recent versions not fully compatible with MySQL; Initial setup could improve|
|SQLite||Relational (Embeddable)||Zero-configuration; Serverless; Self-contained; Transactional SQL database engine||Highly reliable; Compact size; Compatible with popular programming languages||Limited scalability; No built-in data encryption techniques|
|InfluxDB||Time-series||Designed for real-time visibility; Scalable; Allows fast input of data||Scales well; Allows database clustering without a DBA; Input data at any speed or interval||Documentation could be improved; Limited out-of-the-box security; Lacks tools for context to performance issues|
|H2 Database||Relational (Embeddable)||Coded in Java; SQL compliant; Can run as an in-memory database||Extremely lightweight; Easy to setup; Good for small businesses and software applications||Community-based support; Not fully developed; Lacks support for some NoSQL databases|
Let’s see these in detail, one by one:
MySQL is arguably the most popular open source embedded and relational database in the market today. It is now owned by Oracle and is supported by almost every framework or CMS in existence.
Many of the world’s biggest and fastest-growing companies like Google, Facebook, Adobe, Zappos, and Alcatel Lucent depend heavily on MySQL to save money and time while powering their high-volume websites, packaged software, and business-critical systems.
MySQL is well-known for being easy to manage and configure. It works fast, provides effective services, and readily integrates with various development tools like IntelliJ Idea. It is also an ideal solution for an enterprise-level DB with a relatively low cost.
However, it is important to note that MySQL needs significantly high memory to process. It is difficult to debug and maintain the data within and is an expensive tool that may not be affordable for smaller businesses.
Some customers have reported stability issues with this software as well.
Unlike other NoSQL databases, Couchbase comes with an enterprise-class cloud database that provides all the necessary capabilities needed for business-critical applications on an available and scalable platform. It is built on open standards and combines the best of NoSQL with the familiarity and power of SQL. This paves the way for a much smoother transition from mainframe and relational databases.
Couchbase features an extremely fast NoSQL DB response time (just about a millisecond) and gives you complete control over data security, managing operations costs, and cluster configurations.
It also allows you to easily manage security across different levels. However, its backup and restore facilities are somewhat lacking in terms of speed and performance. Also, the educational documents should contain examples of real-life scenarios.
Redis is an efficient open source in-memory NoSQL database and data structure server which is generally used for support functions like caching. As a result, it is frequently overlooked.
However, it is surprisingly easy to learn and, being entirely based in RAM, is extremely fast in terms of reads and writes. What it lacks in features, it more than makes up for in performance and utility. It comes with a state-of-the-art pub-sub system as well.
Redis is an ideal choice for projects which require caching or have some distributed components. It requires no maintenance operations; it works smoothly after being set up. It also offers support for various kinds of data structures.
That said, Redis does lack administration and monitoring tools. Some users have also faced encoding issues while inspecting data directly with the CLI app.
MongoDB gets its name from the word “humongous”. It is a document-oriented open source database system developed and supported by 10gen.
It belongs to the NoSQL family of database systems as well. Notably, MongoDB does not store data in tables as is commonly done in other “classical” relational databases. Instead, it stores structured data as JSON-like documents with dynamic schemas (a format recognized by MongoDB as BSON).
As a result, the integration of data in some kinds of applications becomes significantly faster and easier.
MongoDB makes it easy and convenient to index and queries smaller documents from a large collection of files. If you aren’t too bothered by the fact that joined collections are usually much slower than in relational DB, then this is a great feature for you.
It also offers excellent tool support, such as the MongoDB Compass. Unfortunately, once your data begins to have relations, the query tends to become more complicated as well.
PostgreSQL, also known as Postgres, is a free-to-use open source object-relational database system, which has actively been in development for more than 30 years now.
Being open source, its cost of initial ownership is much lower than that of MS SQL Server and Oracle. It is well-known for its exceptional performance, reliability, and powerful features. It is readily compatible with SQL and has been designed to support numerous workloads in a versatile manner.
PostgreSQL is readily compatible with various languages and comes with a vast number of resources apart from the many own and third-party tools it is compatible with.
This serves to increase its productivity by a considerable margin. However, there is still room for improvement as far as its support for JSON type and “full vacuum schema” are concerned. Also, the installation process is not uniform across all supported operating systems.
Apache Hive offers extensive support for data querying and analysis of huge datasets stored in various compatible systems, including the Hadoop distributed file system (HDFS).
It is distributed under an open source license and serves as a relatively more economical solution for data warehousing and aggregation compared to its peers.
Apache Hive comes with useful features such as ETL, reporting, and analytics on top of Hadoop file systems. It is also notable for its tabular format and availability of connectors for all cloud platforms.
However, it is not a recommendable choice for online analytical transaction processing systems. Also, shuffling of data results in complex joins taking a longer period of time for execution.
Created by the original developers of MySQL, MariaDB is an open source relational database supported by the MariaDB Foundation and a thriving community of developers. It supports ACID-style data processing with guaranteed consistency, isolation, atomicity, and durability for transactions.
It also supports parallel data replication, JSON APIs, and various storage engines like Aria, Spider, MyRocks, InnoDB, Cassandra, TokuDB, and MariaDB ColumnStore.
Recent additional capabilities of this database include compatibility features with Oracle Database, advanced clustering with Galera Cluster 4, and Temporal Data Tables allowing users to query the data as it stood at any point previously. That said, it is important to point out that recent versions of MariaDB aren’t fully compatible with MySQL, making migration a cumbersome process. Also, its initial setup has room for improvement as far as configurational values are concerned.
SQLite is an in-process library that comes with a zero-configuration, server-less, self-contained, transactional SQL database engine. The code for this database is in the public domain and can readily be used for any purpose – whether private or commercial. It is one of the most widely used databases in the world and finds numerous applications, including a number of high-profile projects.
It is also remarkably compact, with a library size potentially less than 600 KiB depending on the compiler optimization settings and target platform.
Being meticulously tested prior to every release, SQLite is known to be highly reliable. Its code base is supported by an international team of developers who work on the database full-time.
It is also readily compatible with most of the popular programming languages. However, its scalability is limited to small applications. If you are working with a larger data set, then the speed to query data could be decreased. Also, it doesn’t feature any inbuilt data encryption techniques.
InfluxDB is a time-series database developed by InfluxData, which has its headquarters in San Francisco. It has been conceived as a solution for optimal observability and has been designed to offer real-time visibility into systems, sensors, and stacks.
This database is available open source through the Cloud as a DBaaS option or via an enterprise subscription. It scales remarkably well and also allows you to produce a database cluster without involving a database administrator.
InfluxDB allows data to be inputted at any speed or interval, regardless of its volume. It also offers numerous options for configuration and tuning according to your requirements.
However, there is still room for improvement as far as its documentation is concerned. It also has out-of-the-box security limited to an internal network and doesn’t seem to have tools to give context to performance issues such as slow queries.
H2 is an open source, embeddable database management system (RDMS) coded in Java. It is extremely lightweight (with a size of merely 2 MB) and is one of the easiest systems to get started with.
It is an especially good choice for smaller businesses and companies dealing with computer software. Being SQL compliant, it is readily compatible with most relational databases. If required, it can be run as an in-memory database as well.
H2 Database is very easy to set up and only requires a dependency added to the application, apart from a few lines for configuration.
Unfortunately, its support appears to be exclusively community-based as of now. There is also a warning in the “Is It Reliable?” section in its official FAQ which implies that H2 Database isn’t a fully developed product yet. Support for some NoSQL databases would be a great addition to the H2 Database Engine.
Open Source software is highly reliable, continuously evolving, and much more secure compared to proprietary software. It is also remarkably flexible and allows you to modify it in a way that suits your business requirements. You will have complete control over your software and will not be confined by rigid user agreements associated with proprietary software.
However, when it comes to open source database software, there are a lot of options to go through. The list is ever-growing and can be quite overwhelming to go through in its entirety.
In this guide, I have presented ten of the best databases available today that you can use to improve on your solutions, whether you are building for yourself or others. I hope this article proves to be useful and gives you a solid starting point upon which to make your own selection.