What are the two types of data processing in AWS?

The two types of data processing in AWS are batch processing and stream processing.

Batch processing refers to the processing of large volumes of data collected over a period of time. This approach is typically used when immediate analysis is not required, allowing for tasks to run at scheduled intervals. Examples of batch processing services in AWS include AWS Glue and Amazon EMR, which are suited for handling extensive datasets efficiently in a planned manner.

On the other hand, stream processing allows for the real-time processing of data as it is generated. This approach is crucial for scenarios that require immediate insights or decisions based on ongoing data flows. Services such as Amazon Kinesis and AWS Lambda support stream processing by enabling the capture and analysis of real-time data streams, helping organizations respond rapidly to changing information.

Understanding the distinction between these two types of processing is fundamental in data engineering on AWS, as it helps in selecting the right tools and services based on specific business requirements related to data handling.