Question 1

Does TextQL optimize Athena queries to reduce S3 scan costs?

Accepted Answer

Yes. Ana generates queries that leverage partition pruning, column projection, and predicate pushdown to minimize the amount of S3 data scanned. For partitioned tables, Ana automatically adds partition key filters when your question includes time ranges or other partition-aligned criteria, significantly reducing per-query cost.

Question 2

Can TextQL query different file formats in S3 through Athena?

Accepted Answer

Yes. TextQL works with any file format Athena supports — Parquet, ORC, Avro, JSON, and CSV. Ana generates the same natural language queries regardless of underlying format. For best performance and cost, we recommend columnar formats like Parquet, but TextQL handles all formats transparently.

Question 3

How does TextQL connect to Athena?

Accepted Answer

TextQL connects via the Athena API using IAM credentials (access keys or assumed roles). Queries execute within your specified Athena workgroup, and results are written to your configured S3 output location. TextQL manages the asynchronous query lifecycle — submit, poll, and retrieve — behind the scenes.

Question 4

Does TextQL work with the AWS Glue Data Catalog?

Accepted Answer

Yes. TextQL reads your Glue Data Catalog to discover databases, tables, partitions, and column metadata. This means any tables registered in Glue — whether created by crawlers, Spark jobs, or manually — are automatically available for natural language queries through TextQL.

Question 5

Can I combine Athena data with other sources?

Accepted Answer

Yes. TextQL can join Athena query results with data from Snowflake, Postgres, Redshift, or any other connected source. For example, ask "compare CloudTrail login events in Athena with user records in Postgres" and get a single unified answer from both sources.