In this article, we’ll try to do exactly that – help you identify the use cases where you’d use Redshift for your analytic workloads, versus those where you’d lean more towards Athena. Nevertheless, there are some high-level factors you can look at to help you gauge which tech could be the more relevant for your situation. ) Like most cliches, this one is also true technology decisions are rarely black and white and if two platforms are commonly used, it’s often because each can be useful for some users in some scenarios. (we’ve done it too when we compared Kafka to Kinesis. “Tool X vs Tool Y” comparisons usually start and end with a cop-out stating that everything depends on your particular circumstances, there is no single correct answer, etc. The rapid release of new databases and analytics tools – both by AWS and newer players such as Snowflake – can leave software architects baffled as to which stack they should adopt in order to solve a specific business scenario. Redshift has only been commercially available since 2013 Amazon Athena has only been around since 2016. With the near-ubiquity of Amazon Web Services in cloud computing, it’s easy to forget how new many of its services are. Read on for the excerpt, or get the full education pack for FREE right here. The following article is part of our free Amazon Athena resource bundle. Want to master data engineering for Amazon Athena? Get the free resource bundle:.Understanding Athena vs Redshift Pricing.4 Questions to decide where to run your analytic workloads.Redshift or Athena? The super-short answer.
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