![]() To give it a try you can execute sample Athena pipeline templates, or start building your own, in Upsolver SQLake for free. SQLake automates everything else, including orchestration, file system optimization and all of Amazon’s recommended best practices for Athena. We’ll help you avoid these issues, and show how to optimize queries and the underlying data on S3 to help Athena meet its performance promise.Īthena is the most popular query engine used with Upsolver SQLake, our all-SQL data pipeline platform that lets you just “write a query and get a pipeline” for data in motion, whether in event streams or frequent batches. However, Athena is not without its limitations: and in many scenarios, Athena can run very slowly or explode your budget, especially if insignificant attention is given to data preparation. If you want a ton of additional Athena content covering partitioning, comparisons with BigQuery and Redshift, use case examples and reference architectures, you should sign up to access all of our Athena resources FREE.Īmazon Athena is Amazon Web Services’ fastest growing service – driven by increasing adoption of AWS data lakes, and the simple, seamless model Athena offers for querying huge datasets stored on Amazon using regular SQL. This article is part of our Amazon Athena resource bundle. Athena Performance – Frequently Asked Questions.How to Improve your Query Performance by 10-15x.Data Preparation for Athena – Spark vs Alternatives.7 Top Performance Tuning Tips for Amazon Athena.How Does Athena Achieve High Performance?. ![]() SQLake Brings Free, Automated Performance Optimization to Amazon Athena Users.
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