Just five short years ago, we saw a huge surge in interest and innovation around database technologies. You’ve heard the reasons behind this interest a million times, so I won’t get into them, but the result was the rapid development of a number of diverse set of databases. We went from a handful of options to hundreds as the industry weighed different models and tested storage in different shapes, sizes and forms. Forward thinking engineers tested and introduced dozens of new data models, including key-value, column-family and (of course) my favourite: graphs.
We’ve seen relational databases maintain a strong foothold in the market. However, we’ve also seen the emergence of a variety of NoSQL databases that range from niche to mainstream, with countless options in between. As of my writing, DB-Engines counts more than 300 different options – a huge array of choices that points to a significant pain point in the marketplace that customers are looking to solve. However, in a competitive market, that number isn’t going to last forever.
That brings me to my key point: we’re at a crossroads for database technology. When we look to the future, even just five years ahead, the world of data looks entirely different – a natural result of competition in the market as we settle on a select group of databases that have the ability to dramatically change business. I believe that by 2020 we’ll see a fragmentation of databases into three parts:
- The first segment will be the relational world. This segment isn’t going to blow anyone away with its growth numbers, but it is still the dominant technology and isn’t going anywhere fast. There are countless applications and use cases for relational, and countless enterprises still rely on them.
- The second segment, tier one non-relational databases, will be a slice of the industry formerly known as the NoSQL space. In this segment, we’ll see a handful of winners come to the forefront. Many leaders have already emerged – MongoDB for documents, Redis for key value, Cassandra for column family and our own Neo4j for graphs. Although each of these leaders will have their own native data model, I also believe they’ll all offer secondary functionality for other data models as well, leading to some overlap between use cases and increased competition in this segment.
- The last segment will be the tier-two non-relational databases that focus on niche models. These niches include those models that the leaders haven’t had time to invest in – like geospatial, time-series databases and the like. Inevitably, due to the smaller use cases and boutique models, these will have less of a commercial impact but can still carve out a valuable segment of the market.
What about graphs?
So, that’s where we stand with databases as a whole – but what happens when we zoom in on graphs? Obviously, as the creator of Neo4j I’m somewhat biased towards that model, however, the market has shown inarguably massive growth.
Despite all of the competitors vying for mindshare in the NoSQL space, we’ve seen graph technology take first place as the fastest growing category of database of the last three years (see below from DB-Engines).
To me, 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 par with the data itself. Those relationships are critical. As enterprises become more technologically savvy, we’ve seen that the value of connected data has exploded.
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 rapidly increase.
Organizations around the world are realizing that, in terms of data, a connected enterprise is more effective – and profitable – than a disconnected one. Today, our progress is marked by rapid growth, but I believe that in 2017 and the years beyond, graph technology will become an enterprise standard for every Fortune 500 company.
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