Four general ETL tools categories exist today. As methods, technology, and needs change, new more useful tools may appear. The following generalize most ETL tools.
Batch Processing ETL Tools — Batch processing tools are the de facto method for processing large volumes of data. With these tools, enterprises can process batches of data when it is convenient to do so, like nights, or on weekends when compute power is more available.
Cloud-native ETL Tools — In an evolutionary step, the cloud has eliminated many constraints in ETL. For example, with cloud ETL, applications can extract and load data directly into the cloud data warehouse, no need for batch processing.
Open Source ETL Tools — Open source tools bring the advantages of community development, and low-cost software, to those data teams on a budget. However, open source tools often only address one aspect of ETL, such as just the Extract stage, and may require multiple tools to achieve transformation goals.
Real-Time ETL Tools — Certain situations demand real-time ETL tools. For example, the Finance industry requires lighting processing in real-time to maintain businesses, and the whole economy. Leveraging the cloud, and sophisticated applications, ETL can be turned into streaming ETL for today’s time-sensitive requirements.