Event driven ETL vs batch driven ETL
In the world of data integration, ETL (extract, transform, load) processes play a foundational role. There are two main types of ETL: event driven ETL and batch driven ETL. While both have their advantages and disadvantages, the choice between them largely depends on the use case and specific requirements of your organization. In this article, we will explore the differences between event driven ETL and batch driven ETL, and their respective pros and cons.
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Event-driven ETL (Extract, Transform, Load) is a data integration approach that processes data in real-time or near real-time based on specific events or triggers. Unlike traditional ETL processes, which typically run on a scheduled basis (e.g., hourly or daily), event-driven ETL responds to events as they occur, making it more dynamic and responsive to changes in data.
The terms data-driven and event-driven refer to different approaches and methodologies used in software design and architecture, particularly in how systems process information and respond to changes. While Event-driven architecture (EDA) focuses on responding to events as they occur. Events can be any significant changes or occurrences in the system that trigger specific actions or workflows.
Event-driven ETL consists of multiple stages. Initially, data is extracted from source systems as events occur, ensuring real-time access. Next, the extracted data undergoes transformation to align with the specifications of the target system. Finally, the modified data is loaded into the target system, enabling immediate analysis.
