As the SQL monolith splinters, developers are ending up with increasingly more data handling options; programmer website DB-Engines counts more than 300 different options.

That’s a great array of choices, and choice is good. But it’s a number that also shows the complexity of the problems organisations are looking to solve in the information age.

However, it can’t continue in this vein – that’s not how markets work, so consolidation and market transformation are clearly coming.

However, the question for the CIO, who needs to make the largest bets on technology, is who will emerge as the Oracle or DB2 of tomorrow. By 2020 there’ll be a fragmentation of the database world into three parts.

The relational world

There are countless business and transaction-heavy applications and use cases for relational, and many enterprises still rely on SQL databases. This isn’t going away.

Tier one non-relational databases

In that part of the industry formerly known as the NoSQL space, there’ll be a handful of winners (like MongoDB for documents, Redis for key value, Cassandra for column family and Neo4j for graph databases).

>See also: The benefits of graph databases in relation to supply chain transparency

Although each of these leaders will have their own native data model, they’ll all offer secondary functionality for other data models as well, leading to some overlap and increased competition.

Tier-two non-relational databases

These will be platforms that focus on niche models like geospatial, time-series databases and the like.

Inevitably, due to their less horizontal use cases and niche business models, these will have less commercial impact, but can still carve out a valuable database market in their own right.

However, what happens when focusing on the graph database sector. There’s no question that the market has shown considerable growth.

It has witnessed graph technology taking first place as the fastest growing category of database for the last three years – according to DB-Engines.

What propels this growth and graph technology’s commercial success is the belief that relationships between data are cherished and treated like first-class entities, on a par with the data itself.

Those relationships are critical. And as enterprises become more technologically savvy, the value of connected data has exploded.

>See also: Living the graph: how graph databases fit into everyday life

The world’s top businesses are looking to connect everything – supply chain, CRM, marketing technology, logistics, customers, payment history – making the value of these connections increase exponentially.

In particular, in a digitised age, powerful, real-time, recommendations and personalisation engines have become fundamental for creating superior user experience and commercial success.

It’s happening right across the economy. As sectors like broadcasting shift towards streaming, content discovery and personalised recommendations become crucial for user experience and engagement; for retailers, effective product recommendation algorithms have become the new standard in online retail, directly affecting revenue streams and the shopping experience.

In logistics, recommendations allow companies to save money on routing and delivery, and provide better and faster service.

Meanwhile, dating apps and social networking software rely equally heavily on personalisation and recommendation engines for optimising the user experience.

In hospitality, dynamic pricing engines allow businesses (i.e. hotel chains) to calculate and optimise personalised prices. In financial services, recommendation algorithms are increasingly important in choosing assets on the modern trading floor, as well as mitigating risk.

The list genuinely goes on and on when it comes to applications for the power of graph technology.

CIOs around the world are realising that, in terms of data, a connected enterprise is more effective – and profitable – than a disconnected one.

>See also: Graphs and smart cities: a neat combination

In a digital economy, recommendations are so important as there’s an ocean of possibilities and choices. After all, how do you create personal relevance when your inventory consists of 250 thousand products and configurations?

This has become a challenging task from a data processing perspective, especially if you’re using a traditional relational database infrastructure. But it’s what the market wants and customers demand.

In 2017 it is likely, therefore, that graph technology will become an enterprise standard for every Fortune 500 company.

Sourced by Emil Eifrem, CEO, Neo Technology