ETL Tool Types Explained

by Katherine VasilegaNovember 12, 2010

Today, I’d like to continue talking about how to choose the appropriate ETL tool for your data integration or data migration needs. To make the right decision, you need to understand the types of ETL tools available on the market. ETL tools can be classified according to their function, engine type, data sources, development environment, and metadata support.

Function: Many ETL tools have either strong transformation or strong cleansing capabilities. If your data can potentially be corrupted, make sure your ETL tool has strong cleansing capabilities. Logically, if various data transformations are a higher priority, pick a tool that is strong in transformation.

The Engine Type: ETL tools can be server engine or client engine. The server engine ETL tool allows execution of multiple concurrent tasks from several computers. The client engine ETL tool is simpler and assumes that the ETL routines are developed and executed on the same machine.

Development Environments: ETL tools can be GUI- based or code-based. Code-based tools are dependent of the language they represent. Aside from general programming languages, several tools on the market utilize a custom-scripting language developed for the optimization of ETL processes. GUI-based ETL tools enable to remove the coding layer and allow non-technical users generate ETL processes.

Data Source: As there are many types of data sources, for each organization, there will be a different set of them. Make sure that the ETL tool you select can connect directly to your source data.

Metadata Support: ETL tools play a key role in your metadata management, because they map the source data to the target. Data mapping rules by themselves are an important piece of the metadata. It is crucial to select an ETL tool that works with your general metadata strategy.

In general, ETL tools depend on your business needs and technical capabilities. The best way to decide which ETL tool is going to work for your organization is to conduct a deep analysis of your data integration or data migration needs with a help of qualified professionals.

Take a look at Apatar in the course of evaluation.

“In collaboration with Apatar, we came up with a dynamic stock market simulation project which exceeded expectations. Being highly satisfied and grateful, we would recommend Apatar to anyone who needs to solve data integration issues across their projects.” —Rakesh Varna, National Institute of Technology, Karnataka