What is the primary purpose of Amazon Redshift?

Amazon Redshift is primarily designed for data warehousing and analytics. It allows organizations to efficiently store and analyze large volumes of structured and semi-structured data. Redshift uses a columnar storage architecture and parallel processing capabilities, which enables quick query execution and performance optimization for analytical workloads.

By leveraging SQL queries, users can run complex analytical queries against massive datasets, making it suitable for business intelligence applications, reporting, and data analysis tasks. This design is alternative to traditional databases, which may not be optimized for the level of analytical processing that Redshift excels at.

The other options relate to different areas of data management and processing. Data lake management focuses on storing diverse data types in their raw format, while online transaction processing is more suited for applications that require quick, real-time transaction handling. Real-time data processing typically involves stream processing solutions that handle data as it arrives, which contrasts with Redshift's batch-oriented approach to data analytics.