SQL is not confined to the traditional relational database systems (RDBMS) and data warehousing solutions. SQL-on-Hadoop engines run on top of distributed file systems to help process big data and ...

BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow.

Databricks Spark ETL Pipeline This project demonstrates an end-to-end Extract, Transform, Load (ETL) pipeline using Apache Spark on the Databricks platform. It reads raw data from a CSV file, ...

Microsoft first truly disrupted the ETL marketplace with the introduction of SQL Server Integration Services (SSIS) back with the release of SQL Server 2005. Microsoft has upped the ante yet again by ...

This project demonstrates an end-to-end ETL pipeline using Databricks + PySpark on a retail dataset (Sample Superstore). It follows the Medallion Architecture (Bronze → Silver → Gold) and shows how ...

ETL jobs can be written in a programming language like Java, in Oracle’s PL/SQL or Teradata’s SQL, using platforms like Informatica, Talend, Pentaho, RedPoint, Ab Initio or dozens of others.

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.