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 ...

Create the ETL Jobs We can finally focus on the process of transforming the various sources of data. Here again, multiple technologies exist: MapReduce, Cascading and Pig are some of the most common ...

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 ...

Queplix Corp., a provider of data virtualization solutions, has announced two new product families to bring the benefits of data virtualization to ETL (extract, transform and load). According to ...

Here are common strategies for this process: 1. Version Control For ETL Code Change tracking detects changes in ETL code, ensuring a comprehensive record of modifications made over time.

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

VirtualETL™ and CloudETL™ radically simplify the ETL process, enabling users to configure Queplix's Application Software Blades™, providing easy and automatic connections to target ...

Domo (Nasdaq: DOMO), the AI and Data Products platform, today announced enhanced cloud integration capabilities with ...

If you're considering using a data integration platform to build your ETL process, you may be confused by the terms data integration and ETL. Here's what you need to know about these two processes.

What are the main differences between ETL and ELT? Use our guide to compare ETL and ELT, including their processes, benefits and drawbacks.