The range of databases now in use expands far beyond the traditional ‘Big Four’ – SQL Server, MySQL, PostgreSQL and Oracle. While it is now more common to use an array of database platforms, a distinctive pattern emerges when examining the number of instances in active use.

The Big Four databases maintain their stronghold, asserting dominance notably as the number of instances surpasses 10 and particularly when dealing with 20 instances or more. Surprisingly Microsoft Access, while less advanced, it’s been around for over 25 years, and remains the most widely used desktop, team and SMB database. A database platform may be chosen to be adopted for a variety of reasons, but the top three requirements were: accuracy, ease of use and cost.

While the array of database platforms in use reveals one part of the story, the length of time explains another. Predictably, the traditional ‘Big Four’ – SQL Server, MySQL, PostgreSQL and Oracle – are the databases that have all been in use the longest, along with IBM DB2 and Microsoft Access.

While they continue to attract new users, with PostgreSQL in particular being very popular, other databases are catching up fast such as Cassandra, MongoDB, ElasticSearch and Aurora.

As different and more complex data prompts IT teams to look for the best database platform for particular use cases, they are now far more willing to go beyond their legacy database platform. To PostgreSQL and MySQL for relational data, and to NoSQL alternatives like Cassandara and MongoDB when it’s semi-structured or unstructured data.

Traditionally, the type of data stored in databases has often been structured data. However, with the rise of big data and the increasing variety of data sources, there has been a shift towards incorporating semi-structured and unstructured data into databases, requiring the use of different database types and platforms to effectively manage and analyze these diverse data formats.

As might be expected, SQL Server, Oracle, MySQL and PostgreSQL are the most favored databases for storing relational data.

For semi-structured data, open-source databases like MongoDB, Redis, PostgreSQL and ElasticSearch make an appearance. SQL Server, however, takes the number one spot in this category as well. This type of data is commonly used where variability in data structure is expected.

For unstructured data, MongoDB proved the most popular. Allowing developers to store and manage data without a predefined structure makes it particularly suitable for applications with evolving or dynamic data models.

As for Geospatial and Graph data, NoSQL databases dominate, apart from IBM DB2 which remains a strong contender thanks to its DB2 Spatial Extender and Db2 Graph capability.

When respondents were asked which specific factors influenced their decision to adopt multiple database platforms, both differing use cases and the need to increase flexibility score more than saving costs. This disputes the often-suggested reason that open-source databases like PostgreSQL are rising in prominence merely for cost-savings.

In addition to the above, the fourth most popular factor in implementing a multi-platform environment was not anticipated: meeting vendor requirements. It appears that as businesses adopt new technologies and applications, they are sometimes required to use a particular database. WordPress, for example, uses MySQL by default as its database management system, and internal business applications like accounting packages may only be available on a particular tech stack like SQL Server and Windows.

The use of multiple database platforms impacts teams across the Organization, but there’s an interesting division emerging. Among those engaged directly in database management such as Developers and DBAs and IT/Ops, nearly half (48%) are working across databases. When we look at those more involved with internal business processes like infrastructure and BI, security and Site Reliability Engineers, it falls to 23% and then drops to 11%.

This would suggest that those most impacted by working with multiple databases are at the forefront of development.

Adopting multiple databases to optimize business processes provides many advantages, but using multiple databases requires a versatile skill set that spans various technologies, architectures, and operational practices. Among the respondents who use more than one database platform, skillset requirements was selected as the number one challenge.

The effects of which spread across all areas of data management. Businesses face the dual challenge of optimizing their operations for efficiency while needing to bridge the skills gap to effectively leverage new technologies.

Introducing new database platforms to existing infrastructure significantly increases the complexity of data management processes. The differences between database platforms are vast, from programming languages and data models through to architecture and features, there is no one size fits all. While the increasing quantity of data, and kind of data, every organization is now faced with has its benefits, it also makes database estates more complicated and demands more knowledge from those tasked with managing the multiple database types now in use.