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October 12, 2010

ETL Alternatives: ELT

Filed under: ETL — Tags: , — Katherine Vasilega @ 8:06 am

With plenty of data integration strategies to choose from, most organizations automatically look for an ETL (extract-transform-load) data integration tool. However, depending on the particular business needs, a company may require a different method for their data integration initiative, such as data federation, ELT, and real-time data integration. Today, I will talk about ELT (Extract, Load, and Transform) technology.

ELT method is also known as in-database integration. With this process, most of the data transformations occur after the data has been loaded into the target database. The order of transforming the data is the main difference between ETL and ELT. It leads to some other major differences:

• ETL functions at the integration server level, while ELT functions at the infrastructure level, using SQL and related procedural features of the relational database to optimize performance.
• Transforming the data after it has reached the target helps minimize costs, because software licensing and development costs in Data Warehousing initiatives can be much larger than the costs of infrastructure.
• ELT method leverages the convenience of virtualization and cloud computing, which helps to speed up processes.

Choosing the right method is quite subjective, and people tend to stick to what they know. However, you can begin by carefully analyzing the requirements related to functionality, volumes, performance, and costs of both technologies.

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