Data Ingestion Framework enables data to be ingested from and any number of sources, without a need to develop independent ETL processes for each source.
This framework provides a set of ETL processes that are used to ingest data from any source into any target by leveraging the metadata-driven approach, therefore lessening the overall development time, maintenance requirements, and reducing the complexity by effective error handling mechanism with audit and control.
For typical data lake projects, organizations need to ingest data from several varied data sources to a landing zone to be integrated into downstream applications. In most cases, organizations build ETL or ELT jobs for each source, which creates challenges.
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Data Ingestion Framework High-Level Architecture
Artha's Data Ingestion Framework
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Key Aspects of Data Ingestion Framework
Performance of Dynamic Ingestion Framework
Horizontally Scalable
ETL process run with better performance
Increase the performance of ETL by more than 200%
