Is there a better way to run and explore Athena queries than the AWS console?

Other options include using Athena through Python with a compatible client library, or connecting business-intelligence tools that support Athena. For your use case, though, a JDBC-enabled SQL editor is probably the quickest improvement: it lets you explore several statements side by side without constantly changing console tabs.

Athena is designed as a SQL layer over data in S3, not as a conventional always-running relational database. Each query can involve distributed work and substantial S3 reads, so it won’t feel as responsive as a local connection to SQL Server or another traditional database. A desktop client will fix the console’s usability issues, but it won’t eliminate the underlying query latency. Partitioning data, selecting only needed columns, and using columnar formats such as Parquet can help performance.

If the data is in S3 and you’re already querying it with Athena, you don’t have to use the AWS console. Athena supports JDBC, so you can connect it to a SQL client such as DBeaver. That gives you multiple editor tabs, query history, saved scripts, and a much more familiar workflow. You’ll need the Athena JDBC driver plus the appropriate AWS credentials, region, catalog, database, and S3 query-results location.