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ETL vendors benchmark their record-systems at multiple TB (terabytes) per hour (or ~1 GB per second) using powerful servers with multiple CPUs, multiple hard drives, multiple gigabit-network connections, and much memory. In real life, the slowest part of an ETL process usually occurs in the database load phase.
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format.
Spatial extract, transform, load (spatial ETL), also known as geospatial transformation and load (GTL), is a process for managing and manipulating geospatial data, for example map data. It is a type of extract, transform, load (ETL) process, with software tools and libraries specialised for geographical information.
Data loading, or simply loading, is a part of data processing where data is moved between two systems so that it ends up in a staging area on the target system.. With the traditional extract, transform and load (ETL) method, the load job is the last step, and the data that is loaded has already been transformed.
Scriptella is an open source ETL (Extract-Transform-Load) and script execution tool written in Java. It allows the use of SQL or another scripting language suitable for the data source to perform required transformations.
Crosswalks also have several technical capabilities. They help databases using different metadata schemes to share information. They help metadata harvesters create union catalogs. They enable search engines to search multiple databases simultaneously with a single query.
Microsoft SQL Server Integration Services (SSIS) is a component of the Microsoft SQL Server database software that can be used to perform a broad range of data migration tasks. SSIS is a platform for data integration and workflow applications. It features a data warehousing tool used for data extraction, transformation, and loading (ETL).
Staging area architectures range in complexity from a set of simple relational tables in a target database to self-contained database instances or file systems. [4] Though the source systems and target systems supported by ETL processes are often relational databases, the staging areas that sit between data sources and targets need not also be ...