The Need for Speed
Over the past few years, we have seen Hadoop emerge as an effective foundation for many organizations’ big data management frameworks, but as the volume and varieties of data increase, speed continues to be a challenge. More and more of our customers are embracing Big Data, and the value of their investment is dependent on (and limited by) how quickly they can take data to action. We’ve been listening to our clients to understand how we can innovate to stay ahead of the curve to help solve these challenges. Apache Spark grabbed our attention because it addresses many of the limitations of Hadoop’s traditional functionality. Plus, Spark is simply impossible to ignore. The active, growing community of developers and enterprises that have adopted Spark has made this project the hottest open source item from the last year. We want to see the open source community continue to flourish and are excited to see Spark open doors for our customers as the application ecosystem grows and reaches wider audiences.
MicroStrategy Analytics Platform Certified on Spark
As a leader in enterprise BI and analytics, MicroStrategy is devoted to helping people maximize the value of their data quickly and easily. With this in mind, we are excited to say that MicroStrategy Analytics PlatformTM is one of the first comprehensive enterprise-grade BI and analytics platforms to be officially certified to work with Apache Spark through the Databricks “Certified on Spark” program. On top of this, MicroStrategy has decided to begin a key partnership with Databricks—the creators, advocates, and community-drivers of Spark. This was a no-brainer for us. We share Databricks’ belief that widespread adoption of Spark will be a huge benefit to the community. Also, this partnership will facilitate close collaboration and deep integration of our technologies in the long run. Microstrategy’s certification with Spark is just the first step of a hopefully long, productive relationship. We are thrilled to be an early adopter of Spark and excited for this journey.
Running Microstrategy on Spark can be boiled down to three significant advantages: speed, ease-of-use, and enhanced advanced analytics. By running MicroStrategy on top of Spark, users will be able to accomplish data analytics projects up to 100x faster. The key is Spark’s in-memory processing, which avoids the constant access to the disk required by MapReduce, a costly and time-consuming exercise. Spark has native support of Java, Scala, and Python and requires far less coding for comparable Hadoop jobs. Also, Shark (Hive on Spark) delivers real-time query capabilities for improved ad-hoc data exploration, making Hadoop reasonably interactive for the first time. Spark’s fully unified platform provides a wide array of advanced analytics capabilities as first-class citizens, including streaming data support, machine learning, and graph computation. These features benefit end-to-end application performance and reduce decision latency—in other words, once data is available, users can uncover insights and act, faster. In effect, users can enhance and fine-tune the performance of their big data framework and as a result get more value from their data at every level.
Customers will benefit enormously from Spark/MicroStrategy integration, and some are already leading the charge: Yahoo! Taiwan is currently using Spark/Microstrategy configurations in a testing environment. This partnership is an extension of MicroStrategy’s commitment to giving our clients the most comprehensive advanced analytics and business intelligence solutions that not only provide fast visual insights on Big Data, but also carries enterprise-class scalability, reliability, and data governance.
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