However, there are differences in how they work under the hood. We’ve written quite a lot about Athena in the last few years, so you can check out our Amazon Athena resources here.īoth Spectrum and Athena are similar in that they both enable you to query data stored on S3. It is fully managed so there is no infrastructure to maintain – simply define and run your query. Spectrum enables you to query data stored on Amazon S3 using SQL, and to run the same queries on tabular data stored in your Redshift cluster and data stored in S3 – all using the Redshift SQL query editor.Īmazon Athena was introduced in 2016 as a standalone, serverless SQL query engine used to query data stored on Amazon S3. The ContendersĪmazon Redshift Spectrum was launched in April 2017 as a feature within Amazon Redshift. Let’s proceed to take a closer look at Athena and Spectrum, with the aim of understanding when you should choose each tool for a specific analytical workload. However, a closer look will reveal key differences between these two services – which could manifest in cost, performance and functionality. Ostensibly, both of these services are used to query data from Amazon S3 using SQL, without managing infrastructure. It’s easy to get confused when comparing Amazon Athena and Amazon Redshift Spectrum. Read on for the excerpt, or get the full education pack for FREE right here. The following article is part of our free Amazon Athena resource bundle. Improve Performance and Reduce Costs with Data Lake ETL.Redshift Spectrum: Frequently Asked Questions Choosing between Redshift Spectrum and Athena.
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