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Athena Vs Spectrum. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. A query in Athena and Spectrum generally has the same cost basis of 5 per terabyte scanned. Athena can scale up to as large as it needs to for bringing back your query results in seconds if desired. In AWS there is a suite of tools that make analyzing and processing large amounts of data in the cloud faster including ways to optimize and integrate existing workflows with Amazon S3.
Parquet is a columnar data format that provides superior performance and allows Redshift Spectrum or Amazon Athena to scan significantly less data. AthenaGlue Catalog can be used as Hive Metastore or serve as an external schema for Redshift Spectrum Amazon Redshift Vs Athena Scope of Scaling Both Redshift and Athena have an internal scaling mechanism. Assuming you have objects on S3 that Athena can consume then you might start with Athena vs. It also integrates with AWS Glue so you can identify the schema of your data sources as well. 1972019 Athena is serverless similar to Lambda so it means that you dont have any infrastructure to spin up or manage for computing your queries. Redshift Spectrum runs in tandem with Amazon Redshift while Athena is a standalone query engine for querying data stored in Amazon S3.
It also integrates with AWS Glue so you can identify the schema of your data sources as well.
Athena allows writing interactive queries to. 1972019 Athena is serverless similar to Lambda so it means that you dont have any infrastructure to spin up or manage for computing your queries. Let us consider AWS Athena vs Redshift Spectrum on the basis of different aspects. 2172020 Spectrum is a feature of Redshift whereas Athena is a standalone service. It also integrates with AWS Glue so you can identify the schema of your data sources as well. Athena supports it for both JSON and Parquet file formats while Redshift Spectrum only accepts flat data.