The focus in the Analytics & BI market is on beautiful visuals and things like Artificial Intelligence. One would nearly forget that you need a solid backbone to have all the underlying data well prepared to your disposal. This last bit is labeled the Data Integration market and Gartner recently released its Magic Quadrant for 2019. This assessment should help data and analytics leaders make the best choice for their organization.
When comparing the quadrant position of the vendors throughout the years, there actually is little movement in the quadrant of Data Integration. Use the fully interactive Power BI reports below to visualize the movement in both markets. The Data Integration market appears to be standing still whilst the Analytics & BI market is all over the place. But is it really?
Analytics & BI market movement
Data Integration market movement
The market in detail
It looks to be a done deal in the Data Integration market, as Informatica and IBM are still going strong in the leaders segment. However, it is noticable (in the top right visual) that Attunity moved up quite a bit, which undoubtadly contributed to the acquisition by Qlik. Actian is declining heavily, and it is questionable if they are seen in next year’s quadrant. Next to that, Denodo increased rapidly in the last 3 years, whilst they primarily focus on Data Virtualisation. That raises the question what Gartner acutally sees as the Data Integration market. Ab Initio is missing for years in the Gartner quadrant, whilst this is seen as the absolute best tooling by the Ab Initio community. Of course this is not the only missing tool. Gartner provides a detailed report with remarks per vendor and vendor selection criteria, but this does not mean only these tools will be suitable. In the end, it is all about the specifics of tools that are relevant or not for your organisation. A glance at the quadrant should not result in the conclusion that Informatica or IBM are the best tools for your organisation. Some organisations even can do without any of these (sometimes very pricy) tools, as a lot of the their functionality has found its way to database platforms. Make sure to be properly informed.
Now then, has the Data Integration really come to a halt by lack of movement? Well, the positions in the quadrant are relative to market demand. So if sufficient requirements are included in the tool or vision of a vendor, that vendor would hardly change position. As a result, everyone seems to have done their job, but mainly with regard to vision (see the bottom right visual). Nevertheless, this level remains far below that of 2017 and we are not yet above the dip of 2018. In the Analytics & BI market there is much more movement detected. This can be explained by the greater demand for new functionality which vendors comply to in greater or lesser extent with tools or vision. So there is simply much more to do about functionality and its implementation by vendors in that market.
Despite the limited shifts in the Data Integration quadrant, it could still be the case that heavy requirements have been put on the table. Gartner speaks of a resurge in the market, and has prominently stated the following components:
hybrid / intercloud integration
This should, amongst others, make cloud service integration easier. Well, that’s about time, since there have been cloud providers around for quite some time. Keep in mind though, that combining data from multiple cloud providers and data "on premise" always remains a challenge in an infrastructural and application kind of way. Analogy for infrastructural: under water you can simply breathe better through a bamboo stick than through a straw. Analogy for applicative: if you have a straw or bamboo to your disposal, but are only allowed to breathe in a specific way and for a short time. By the way, "on premise" often does not mean "servers in the basement of the organization", but servers at a hosting party. In many cases you can also see that as "cloud infra". The tools therefore only solve part of the cloud integration issue.
active metadata & augmented data management
Although these points are prominent, these types of requirements have been on the shelf for quite a long time. They are named separately by Gartner, but have a lot to do with each other. Consider, for example, the automatic implementation of source changes in the analytical environment. But also discovering any privacy rights issues. Machine Learning is now being used more and should pave the way for very powerful solutions together with Graph analytics. But that is currently more a vision than reality.
The Data Integration market is not standing still, but is less hectic in terms of functionality than the Analytics & BI market. The tools and vendor vision develops nicely along with market demand. This is sufficient on its own, because this allows for requirements of organizations to be met. However, I would say there is a resurge, because the functionality offered should have been available earlier to my opinion. For the time being, we must primarily accept the vision, and to a lesser extent concrete tooling, as added value.