The big data community was rocked last week when news broke that Cloudera and Hortonworks would merge, forming a new $5.3 billion company. I spoke to several reporters shortly after to give them Unravel’s perspective on the merger as CEO of a company that’s long supported both platforms. Our discussions covered various interesting threads but ultimately ended up in the same place: this merger essentially means business as usual for big data.
Cloudera and Hortonworks were formed on the premise that big data was for everyone, not just web giants like Amazon and Google. The two were fierce rivals for many years, which was good because it drove both to innovate and continually differentiate their respective platforms. They both aggressively sold their platform and services to enterprises, helping big data become mainstream over the past five years. However, they also spent a great deal of energy lining up against each other, instead of directing that energy toward customer challenges. As a merged entity, that energy and redundancies can likely be eliminated, and the new company can focus on what they both have done best: helping enterprises to store, manage and monetize their data.
Some in the industry mistakenly thought this merger might mean that the two companies were struggling, and big data adoption is faltering, pointing to the flattening of the growth curve for on-premise Hadoop as a proof point. The truth is that big data continues to evolve, and this merger reflects the transition of a new phase for the industry. Deployment models continue to evolve and migrate to cloud in its various forms of hybrid and multi cloud configurations and whilst definitions of ‘Big Data’ can be ill-defined, growth in big data technologies such as Spark, Kafka and Cassandra continue to surge at a rapid rate.
The conversation around big data used to focus on which systems and platforms to deploy, and that’s where the debate of Cloudera vs. Hortonworks raged. Now, the conversation’s moved past that and instead is focused on how to draw out insights and create new applications (particularly AI and machine learning apps) that leverage these systems and solve a business problem worth solving. Companies have their data lakes, now they want to extract and monetize the value buried within. The big data landscape will always be in a constant state of change, where established technologies like Hadoop will mature while growth shifts to Spark, Kafka, Cassandra, and Flink, for example. That change is the sign of a strong ecosystem adapting to meet emerging needs.
Unravel was built to sit on top of all these systems, providing a single pane of glass to manage performance of all big data platforms today and in the future. We’ve assumed changes like this are inherently native to our ecosystem and crucial to stimulating innovation and advancement. Our platform is designed natively to extend and adapt to these shifts and we’re constantly adding support for new big data technologies and means of deployment. Along with the rest of the ecosystem, we’ll absorb whatever decisions are made as the merger closes and the rationalized platform emerges and we’ll be prepared to ensure our customers are not negatively impacted. In fact we already are. It’s what we do.
We continue to believe in the promise of big data and we remain committed to our mission of radically simplifying the planning and management of business-critical modern data applications, and guaranteeing the performance, reliability, and cost of the big data systems they rely on. The Cloudera-Hortonworks merger caught many (but not all) by surprise and certainly caused some ripples in financial markets, but for Unravel customers who use and depend on these technologies every day, it’s nothing more than business as usual.