However if you are using Redshift, it would likely make more sense to use Spectrum in this case. Athena also has a Redshift connector to allow for similar joins. If you are working with Redshift, then Spectrum can join information in S3 with tables stored in Redshift directly. The functionality of each is very similar, namely using standard SQL to query the S3 object store.

Federated query capabilities: Both support federated queries.

Schema management: Both use AWS Glue for schema management, and while Athena is designed to work directly with Glue, Spectrum needs external tables to be configured for each Glue catalog schema.

They run $5 per compressed terabyte scanned, however with Spectrum, you must also consider the Redshift compute costs.

Pricing: The cost for both is the same.

Query types: Athena is great for simpler interactive queries, while Spectrum is more oriented towards large, complex queries.

Consistency: Spectrum provides more consistency in query performance while Athena has inconsistent results due to the pooled resources.

Standalone vs feature: Redshift Spectrum runs in tandem with Amazon Redshift, while Athena is a standalone query engine for querying data stored in Amazon S3.

If you need a specific query to run more quickly, then you can allocate additional compute resources to it.

Performance: Performance for Athena depends on your S3 optimization, while Spectrum, as previously noted, depends on your Redshift cluster resources and S3 optimization.

Cluster management: Spectrum actually does need a bit of cluster management, but Athena is truly serverless.

Athena, however, relies on non-dedicated, pooled resources.

Pooled vs allocated resources: Both are serverless, however Spectrum resources are allocated based on your Redshift cluster size.

S3 storage is significantly less expensive than a database on AWS for the same amount of data. This also is more cost-effective as there is nothing to set up and you are only charged based on the amount of data scanned. Key Features & Differences: Redshift vs AthenaĪthena and Redshift Spectrum offer similar functionality, namely, serverless query of S3 data using SQL. This enables you to join data stored in external object stores with data stored in Redshift to perform more advanced queries. It is a serverless query engine that can query both AWS S3 data and tabular data in Redshift using SQL.

Redshift Spectrum is an extension of Amazon Redshift. This also means that the performance can be very inconsistent as you have no dedicated compute resources. It is fully managed by Amazon, there is nothing to setup, manage or configure. This is used to query data stored on Amazon S3. Athena is Amazon’s standalone, serverless SQL query engine implementation of Presto.

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