![]() Compressing your data, using columnar file formats like Apache Parquet, and using partitions can save you a lot of query time and money in the long run.Īmazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud.Ī data warehouse is a repository of databases containing all your data, in a central place. Athena charges based on the data it scanned on S3, around $5 per TB. In the worst case, it took us few hours to get data. Athena is a serverless service for data analysis on AWS mainly geared towards accessing data stored in Amazon S3. We have used Athena with several terabytes of data, AWS says it can easily scale to petabytes of data. Redshift Spectrum is not an option without Redshift. Basically, you have your data in AWS S3, in one of the formats like CSV, TSV, Apache Parquet, JSON, etc, Athena can help you analyze the data within it in some minutes of setup and query it using SQL in a few seconds. Lastly, remember that a key difference from Athena is that access to Spectrum requires an active, running Redshift instance. It is based on Prestodb, developed by Netflix and Facebook. I am periodically reminded by others that Redshift Spectrum and Athena are different. It’s like having an integrated virtual private Athena. Redshift (local storage) In this test, Starburst Presto and Redshift ended up with a very close aggregate average: 37.1 and 40.6 seconds, respectively - or a 9 difference in favor of Starburst Presto. Spectrum allows you read from S3, rather than load data in.but you still need a redshift cluster. And here is a performance comparison among Starburst Presto, Redshift (local SSD storage) and Redshift Spectrum. You don't need the data to be prepared for this, and the original data is never touched. when querying, data is read through the 'lens' of the schema and you are billed only for data consumed. dbt can interact with Amazon Redshift Spectrum to create external tables, refresh external table partitions, and access raw data in an Amazon S3-based data lake from the data warehouse. I really like Redshift Spectrum as an option for Redshift customers, much more so than Athena, because you get dedicated Spectrum nodes - up to 10x the number of your Redshift nodes. Redshift is best used for large and structured datasets. athena is a adhoc query, schema on read product. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. The external tables exist in an external data catalog, which can be AWS Glue, the data catalog that comes with Amazon Athena, or an Apache Hive metastore. What’s right for you?Īmazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. ![]()
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