It’s hard to imagine data warehousing without ETL (extract, transformation, and load). For decades, analysts and engineers have embraced no-code ETL solutions for increased maintainability. Does this ...
Global software house Microsoft is making big data the focus of SQL Server 2019, set for release later this year. A key part is data virtualisation, eliminating complex ETL processes. Microsoft says ...
Microsoft has made SQL Server 2025 generally available. The latest version of the database focuses on built-in AI ...
Microsoft has dabbled in the ETL (extract-transform-load) marketplace for a long time, in fact, almost 2 decades. Way back in the day, SQL Server shipped with a command-line tool known as the Bulk ...
BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow. BlazingSQL is a GPU-accelerated SQL engine built on top of ...
ETL, according to the ETL definition, is nothing more than extraction, transformation, and loading of data. This is a critical step in data warehousing. An easy way to understand this is to look at ...
Data Integration vs ETL: What Are the Differences? Your email has been sent If you're considering using a data integration platform to build your ETL process, you may be confused by the terms data ...
Rockset has honed itself into a cloud-based database that generates real-time operational analytics from streaming data sources via SQL. Today it announced that it’s working with three of the early ...
So I have been tasked with moving a fairly large amount (2.5 million rows) of highly flat denormalized data from Oracle 11g to MongoDB. The data is highly repetive in that a lot of data repeats itself ...
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