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I have just written a blog post about what’s new in SSAS in SQL Server 2017 CTP 2.0

I am very impressed about all the changes Microsoft has done in the product for the last years.

But, I am also very impressed of what is new / enhanced in this CTP regarding to SQL Server on Windows and Linux:

  • support for storing and analyzing graph data relationships
  • resumable online index rebuild
  • Adaptative Query Processing
  • Interleaved execution
  • Batch mode adaptive joins

In addition, some functionality that was previously available in SQL Server on Windows is now available on Linux for the first time. This includes:

  • Additional SQL Server Agent capabilities – Use SQL Server Agent to keep replicas in synch with log shipping.
  • Listener for Always On availability groups – The listener enables clients to connect to the primary replica in an availability group, monitoring availability and directing connections to the replicas.

That is not everything! Citation from the SQL Server Blog:

Another new, key feature enhancement in CTP 2.0 of SQL Server 2017 is the ability to run the Python language in-database to scale and accelerate machine learning, predictive analytics and data science scripts. The new capability, called Microsoft Machine Learning Services, enables Python scripts to be run directly within the database server, or to be embedded into T-SQL scripts, where they can be easily deployed to the database as stored procedures and easily called from SQL client applications by stored procedure call. SQL Server 2017 will also extend Python’s performance and scale by providing a selection of parallelized algorithms that accelerate data transforms, statistical tests and analytics algorithms. This functionality and the ability to run R in-database and at scale are only available on Windows Server operating system at this time.

You can read the release notes here:

The SQL Server Blog blog post can be found here:




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