Comparison of Amazon Athena , Amazon Redshift, Redshift Spectrum, Redshift Serverless
This post will cover the Comparision of Amazon Athena with Amazon Redshift , Amazon Redshift Spectrum, Amazon Redshift Serverless
Amazon Athena is a serverless, interactive query service to query data and analyze big data in Amazon S3 using standard SQL. For more information on Amazon Athena, refer to our post – http://www.cloudinfonow.com/amazon-athena/
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. For more information on Amazon Redshift , refer to our post – http://www.cloudinfonow.com/amazon-redshift-serverless/
|Feature||Amazon Athena||Amazon Redshift|
|Overview||Serverless, interactive query service to query data and analyze big data in Amazon S3 using standard SQL.||Fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools|
|Compute & Scaling||Serverless. Scales your infrastructure as your datasets and number of users grow||Amazon Redshift starts with configured compute capacity, but can scale up/down automatically through Concurrency Scaling Feature.|
Amazon Redshift Serverless introduced recently (Dec 2021) will provide auto scaling capabilities.
|Storage||No data stored in Amazon Athena . Query against already stored data in S3 buckets through external tables.||For Amazon Redshift, Data is stored in Redshift Clusters which is again Redshift Managed storage in S3 buckets.|
For Amazon Redshift Spectrum, query against already stored in S3 buckets through external tables.
|Performance||Highly Performant. Varies by use case. Amazon Athena provides the easiest way to run ad-hoc queries for data in S3 without the need to setup or manage any servers.||Highly Performant. Varies by use case. Fastest query performance for enterprise reporting and business intelligence workloads, particularly those involving extremely complex SQL with multiple joins and sub-queries.|
|Ideal Use cases||Athena is great if you just need to run a quick query on some web logs to troubleshoot a performance issue on your site.||Amazon Redshift is your best choice when you need to pull together data from many different sources – like inventory systems, financial systems, and retail sales systems – into a common format, and store it for long periods of time, to build sophisticated business reports from historical data|
|ACID Transactions||ACID Complain through Governed tables and Iceberg tables||ACID Complaint|
|Cost||Ideal for Adhoc queries due to per TB scan cost||Ideal for consistent data loads and usage through Reserved instances purchase|
|Security||Amazon Athena allows you to control access to your data by using IAM policies, ACLs, and Amazon S3 bucket policies. |
Supports row-level, cell-level, column-level permissions
|Redshift security is built at no extra cost. Redshift has most extensive options for security data at rest and in transit.|
Supports column level permissions.
|Federation||Athena enables you to run SQL queries across data stored in relational, non-relational, object, and custom data sources.||Supports Federation. Federated queries can work with external databases in Amazon RDS for PostgreSQL, Amazon Aurora PostgreSQL-Compatible Edition, Amazon RDS for MySQL, and Amazon Aurora MySQL-Compatible Edition.|
|Machine Learning||Integrated with Sagemaker. You can invoke your SageMaker Machine Learning models in an Athena SQL query to run inference.|
Training and Model build is not supported.
|Integrated with Sagemaker. Simply use SQL statements to create and train Amazon SageMaker machine learning models using your Redshift data and then use these models to make predictions. |