04
Feb
Redshift Vs Athena. Redshift supports only primitive data types. Since data is stored inside the node you need to be very careful in terms of storage inside the node. With Redshift Spectrum you have control over resource provisioning while in the case of Athena AWS allocates resources automatically. 662016 Redshift requires framework management and data preparation while Athena bypasses that and gets straight to querying data from Amazon S3.
Athena stores query results on S3 and they can be loaded into Redshift from there. Spectrum is a feature of Redshift whereas Athena is a standalone service. Athena can scale up to as large as it needs to for bringing back your query results in seconds if desired. Apart from Redshift all other Data Warehouses Snowflake Hive BigQuery Athena supports complex data structures like arrays maps and structs as first class citizens. Redshift uses Postgresql Snowflake BIgQuery and Athena uses ANSI SQL whereas Hive uses its own HQL for querying. 2172020 AWS Athena and Amazon Redshift Spectrum are similar in the sense that they are both serverless and can be used to run queries on S3 using SQL.
This could be a deal breaker for some.
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. 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. Through a dedicated set of resources and unlimited scalability Redshift easily becomes the choice for its higher performance. Redshift supports only primitive data types. 2172020 AWS Athena and Amazon Redshift Spectrum are similar in the sense that they are both serverless and can be used to run queries on S3 using SQL. With Redshift Spectrum you have control over resource provisioning while in the case of Athena AWS allocates resources automatically.