To use Redshift Spectrum, you need an Amazon Redshift cluster and a SQL client that’s connected to your cluster so that you can execute SQL commands. Athena supports the insert query which inserts records into S3. In Redshift Spectrum the external tables are read-only, it does not support insert query.Redshift Spectrum needs an Amazon Redshift cluster and an SQL client that’s connected to the cluster so that we can execute SQL commands.How is Amazon Athena different from Amazon Redshift Spectrum? Redshift Spectrum pushes many compute-intensive tasks, such as predicate filtering and aggregation, down to the Redshift Spectrum layer. Amazon Redshift Spectrum resides on dedicated Amazon Redshift servers that are independent of your cluster. Amazon Redshift SpectrumĪmazon Redshift Spectrum is used to efficiently query and retrieve structured and semistructured data from files in Amazon S3 without having to load the data into Amazon Redshift tables. This use case makes sense for those organizations that already have a significant exposure to using Redshift as their primary data warehouse. Today, we will explore querying the data from a data lake in S3 using Redshift Spectrum. With Athena, there is no need for complex ETL jobs to prepare data for analysis. Athena is serverless, so there is no infrastructure to manage.
Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Once the data lake is setup, we can use Amazon Athena to query data.
In one of our earlier posts, we had talked about setting up a data lake using AWS LakeFormation.
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