Amazon Athena is a serverless, interactive analytics service that allows users to run SQL queries on data stored in Amazon S3. It is ideal for occasional queries on large datasets, as it does not require any server provisioning, configuration, or management. Users only pay for the queries they run, based on the amount of data scanned. Amazon Athena supports various data formats, such as CSV, JSON, Parquet, ORC, and Avro, and integrates with AWS Glue Data Catalog to create and manage schemas. Amazon Athena also supports querying data from other sources, such as on-premises or other cloud systems, using data connectors1.
Amazon Redshift is a fully managed data warehouse service that allows users to run complex analytical queries on petabyte-scale data. However, it requires users to provision and maintain clusters of nodes, and pay for the storage and compute capacity they use. Amazon Redshift is more suitable for frequent and consistent queries on structured or semi-structured data2.
Amazon Kinesis is a platform for streaming data on AWS, enabling users to collect, process, and analyze real-time data. It is not designed for querying data stored in Amazon S3. Amazon Kinesis consists of four services: Kinesis Data Streams, Kinesis Data Firehose, Kinesis Data Analytics, and Kinesis Video Streams3.
Amazon RDS is a relational database service that provides six database engines: Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. It simplifies database administration tasks such as backup, patching, scaling, and replication. However, it is not optimized for querying data stored in Amazon S3. Amazon RDS is more suitable for transactional workloads that require high performance and availability4.
[References:, Interactive SQL - Serverless Query Service - Amazon Athena - AWS, [Amazon Redshift – Data Warehouse Solution - AWS], [Amazon Kinesis - Streaming Data Platform - AWS], [Amazon Relational Database Service (RDS) – AWS], , , , ]
