The advent of digital transformation has brought about a paradigm shift in the way organizations operate, and two crucial pillars of this transformation are
SQL Server Big Data Clusters CU10 brings important new capabilities
Apr 7, 2021 14:16 EDT with 0 comments
With the release of SQL Server 2019, Microsoft brought Big Data Clusters (BDC) for customers as a way to utilize both structured and unstructured data. Running exclusively on Linux containers that are hosted on Kubernetes, these clusters can be deployed both on-premise and on the cloud. Last year, the tech giant released the cumulative update 5 (CU5) for SQL Server 2019, focusing on expanding capabilities offered through BDC.
Today, Microsoft has unveiled the SQL Server Big Data Clusters CU10 release. With this update, a few new important capabilities have been introduced. These have been highlighted as follows:
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In my August 2020 article, “How to choose a cloud machine learning platform,” my first guideline for choosing a platform was, “Be close to your data.” Keeping the code near the data is necessary to keep the latency low, since the speed of light limits transmission speeds. After all, machine learning especially deep learning tends to go through all your data multiple times (each time through is called an
epoch).
I said at the time that the ideal case for very large data sets is to build the model where the data already resides, so that no mass data transmission is needed. Several databases support that to a limited extent. The natural next question is, which databases support internal machine learning, and how do they do it? I’ll discuss those databases in alphabetical order.