If you're just joining us now, please see the previous post for winner numbers 20 to 16. We'll continue to recognize the top 20 companies that accelerated the big data and analytics marketplace this year with a countdown from 15 to 11 here:
15. SnappyData - There has always been a trend in databases to specialize for better performance or better functionality. Some are for OLTP, some for OLAP, some tightly structured, some looser. SnappyData eliminates the compromises with a clever hybrid approach built around Apache Spark and SQL. Best of all worlds, running in-memory for use on streaming data, too.
14. data Artisans - Speaking of Spark and streaming, many say Apache Flink is even better. data Artisans was founded by Flink's creators to manage stream processing at scale and robustly. Streaming isn't just for analytics—it's a way of life for enterprise-grade real-time data operations and applications. When you've got to do it right, Flink is right there.
13. AtScale - Hadoop has many uses, but one of the most intriguing is enabling the data lake to be a complement and/or alternative to the expense and rigidity of traditional data warehouses. AtScale brings not just effective BI on Hadoop, but also a universal semantic layer to simplify data management everywhere. The economics are compelling, as is the elegance of the solution.
12. Arcadia Data - Arcadia also wants to modernize BI for the big data era, with a universal platform that spans on-premises and cloud-based data, be it hosted in HDFS, Hbase, Kudu, S3, or relational databases. Recent advances include visualization of real-time data alongside the historical context, tie in to Solr for search, and recommendations to improve performance for more concurrent users. It's very nice.
11. Unravel - As distributed compute and data analytics platforms continue to proliferate in the enterprise, someone has to manage it all. Herding the heterogeneous cats is Unravel. While Unravel enables operational control over all your clusters, even more significant is their efforts to make "data ops" as much a trend as "DevOps," and streamline the steps to get new applications built, tested, in production, and running smooth as can be.
Congratulations to these five leaders!
Keep your eyes open for the next post where we'll get into the the top 10....