SQL Server on Linux boosts the database market for Microsoft. Support of PolyBase (a feature to work with Big Data providers), In-Memory Optimized SQL Server, Real-time Operational Analytics, the scaling of Python and R Services for Data analytics, Graph database for NoSQL data, JSON support for transparent data interchange format between traditional and non-traditional database systems, Azure Cosmos DB from Document database to distribution database… All this helps leverage SQL Server to almost every extent, in day-to-day activities.

The shift in technology is being driven by increased expectations. The time-to-market is lower when it comes to applications; the competition is fierce. Also, there’s a lot of unstructured data floating in the ether, such as videos, images, audio, etc., which are more prevalent and problematic for traditional databases. And SQL Server 2017 has emerged, attempting to answer these calls.

It does, though, seem to have the potential to be seen as a powerhouse of a number of desirable features. It is a little early to say whether SQL Server 2017 would become an answer to the myriad of requirements we have; it may also require a lot of fine-tuning and improvisation. But it is perhaps safe to say that Microsoft does seem to be taking it seriously and taking the necessary steps.

Evolution of SQL Server towards Digital Transformation

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