The simplicity and the number of components
Significantly reduces costs of developer rates by cutting the time in nearly half to build, pull, and extract data elements.
Highly efficient with little fear of bad ETL acquisition and fewer errors than manual ETL.
Developers have the ability to tap into the core products of Talend and use a community supported and created plugins to match any specific ETL need.
Customized ETL data extractions that are specific to IT developers’ needs.
Whether the ETL project is big or small, Talend open source has a solution for ETL.
Add as you go: developers can adjust ETL on the fly to accommodate new needs for existing data.
Database administrator or higher level programmer can utilize for ETL needs
The memory requirements and the debugging is difficult with the error messages being off from the actual error in the job
Scheduling feature which is very basic one is available with only Enterprise editions and not with open studio distribution of Talend
To make spark streaming and machine learning work in Talend you have to subscribe to the Real time big data package