I’ve written in the past about the opportunity for #Hadoop -as-a-Service ( #HaaS ) – providing self-service provisioning, elastic scaling, and support for multi-tenancy. But in my discussions with customers over the past year, it’s become clear that the opportunity is even bigger than Hadoop. The next big thing in big data is Big-Data-as-a-Service ( #BDaaS ). There are three key trends driving the evolution and emergence of this new BDaaS opportunity: #Apache #Spark and the evolving big data ecosystem. Hadoop recently celebrated its 10th birthday and continues to gain widespread adoption. But in recent years, other new big data frameworks and tools have also gained in popularity. Foremost among these is Apache Spark, the most active open source project in big data. We’re also seeing increased interest in #Kakfa, #Flink, #NoSQL technologies such as #Cassandra, and much more. And there continues to be rapid innovation in the commercial software market for big data – including analytics, ETL, search, log analytics, and other BI tools. Hadoop is still at the forefront (and many of these tools complement and extend Hadoop), but BDaaS is much more than Hadoop. Enterprise adoption of containers and microservices. Container and microservices technology ( #Docker in particular) has taken hold in the enterprise, and the pace of adoption has accelerated over the past year. Like Spark, Docker has become one of the fastest growing open source technologies ever. Application developers have embraced the simplicity and agility of containers, and microservices are a foundation of the DevOps model. Enterprise IT teams have made containers part of their architecture strategy. And the container revolution is now being extended to big data applications.