There are four primary types of ETL tools:
Batch Processing: Traditionally, on-premises batch processing was the primary ETL process. In the past, processing large data sets impacted an organization’s computing power and so these processes were performed in batches during off-hours. Today’s ETL tools can still do batch processing, but since they’re often cloud-based, they’re less constrained in terms of when and how quickly the processing occurs.
Cloud-Native. Cloud-native ETL tools can extract and load data from sources directly into a cloud data warehouse. They then use the power and scale of the cloud to transform the data.
Open Source. Open source tools such as Apache Kafka offer a low-cost alternative to commercial ETL tools. However, some open source tools only support one stage of the process, such as extracting data, and some are not designed to handle data complexities or change data capture (CDC). Plus, it can be tough to get support for open source tools.
Real-Time. Today’s business demands real-time access to data. This requires organizations to process data in real time, with a distributed model and streaming capabilities. Streaming ETL tools, both commercial and open source, offer this capability.
Learn more about ETL tools and different approaches to solve this challenge: