As a result, analytical applications can now be far simpler and need only query the database for analytic results. It introduces a new paradigm where all joins, aggregations and machine learning are performed securely within the database itself without moving the data out, thereby enabling analytics on real-time transactions with great speed and parallelism. SQL Server 2016 simplifies analytics in the way databases simplified enterprise data management, by moving analytics close to where the data is managed instead of the other way around.
And deep analytics on real-time transactions are next to impossible without a lot of heavy lifting. This approach incurs high latency because of data movement, doesn’t scale as data volumes grow and burdens the application tier with the task of managing and maintaining analytical models. Today a majority of advanced analytic applications use a primitive approach of moving data from databases into the application tier to derive intelligence. The integration of advanced analytics into a transactional database is revolutionary. A new platform for intelligent applications
Software applications can now deploy sophisticated analytics and machine learning models in the database resulting in 100x or more speedup in time to insight, compared to deployments of such models outside of the database.
Today we announced the general availability of SQL Server 2016, the world’s fastest and most price-performant database for HTAP (Hybrid Transactional and Analytical Processing) with updateable, in-memory columnstores and advanced analytics through deep integration with R Services. This post was authored by Joseph Sirosh, Corporate Vice President, Data Group, Microsoft.