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Athena Vs Redshift Spectrum. However Redshift Spectrum tables do also support other storage formats ie. With both services claiming to run queries of unstructured data stored on Amazon. As Spectrum is still a developing tool and they are kind of adding some features like transactions to make it more efficient. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
Access to Spectrum requires an active running Redshift instance. Redshift Spectrum is great for Redshift customers. Amazon Redshift Spectrum is a feature of Amazon Redshift. Spectrum can directly join tables stored on Redshift. Httpsamznto2GSxI6ZShweta an AWS Cloud Support Engineer shows you how to create an Amazon Redshift Spectrum. Spectrum is a serverless query processing engine that allows to join data that sits in Amazon S3 with data in Amazon Redshift.
Amazon Athena is a serverless query processing engine based on open source Presto.
Athena is a great choice for getting started with analytics if you have nothing set up yet. Because Redshift Spectrum and Athena both use the AWS Glue Data Catalog we could use the Athena client to add the partition to the table. Amazon Redshift Spectrum is a feature of Amazon Redshift. 31082017 Assuming you have objects on S3 that Athena can consume then you might start with Athena vs. Athena Cost Spectrum and Athena are both charged based on the amount of data scanned when running a query although there is 10MB minimum per query and AWS rounds up to the next megabyte. So Redshift Spectrum is not an option without Redshift.