A million-row CSV, queryable in seconds.
Drop the export. Get typed columns, indexes, and statistics. A comparison that Google Sheets was still processing finished in about seven seconds.
Data · Database
Query every warehouse and file from one SQL interface
Database Studio unifies BigQuery, Postgres, Snowflake, and Databricks in one query interface. Drop a CSV and it becomes a Database asset—queryable in seconds.
A 1M-row CSV compared in about 7 seconds while Google Sheets was still processing.
- BigQuery
- Postgres
- Snowflake
- Databricks in one surface
- CSV → database in seconds
- Indexes and statistics created automatically
- Ephemeral Postgres to 1 TB
- Per-user permissions
The problem
Data lives in four warehouses and a folder
Every question starts with "which tool do I open." The warehouse needs a ticket. The CSV is too big for Excel. The analyst who knows the schema is on vacation. The agent that could answer has nowhere to run the query.
Query it where it is. Or make it queryable in seconds.
How it works
Connect or drop. Query. Send to sheet.
Connect. BigQuery, Postgres, Snowflake, Databricks, Azure SQL, SQL Server, Oracle, Redshift, with each user's own credentials and permissions.
Or drop a file. Excel, CSV, Parquet onto a Computer asset. Athena infers types, creates indexes, runs statistics. A Database asset appears in the interface.
Query. In SQL, or in plain language. Agents run the same queries with the same permissions.
Send to Sheet. Results land in Athena Sheets with a citation to the query. Or into a dashboard, a notebook, or a deck.
People and agents
What people and agents each do
Database. A built-in SQL database for apps, workflows, and agents to read and write. Load a large CSV in seconds.
| Capability | People can | Agents can | Together |
|---|---|---|---|
| Database | Query the database, or let an app sit on top of the database. | Create tables, write records, run queries on request. | Every write attributed; roll back what should not have changed. |
Anything a person can do here, an agent can do with the same permissions, and both land in the same audit trail.
Use cases
Database Studio in production
30 seconds to 500 milliseconds.
Analytical queries on a Database asset were slow on the first version. Driven by a real audit workflow, the agent created indexes and ran statistics; queries dropped to about 500 ms within days.
Ephemeral Postgres, up to a terabyte.
Spin a database up for an analysis and down when you are done. Agent-operable. No ticket.
Notebooks with isolated compute.
Athena-owned Jupyter with SQL cells and per-user volumes on billion-row data. The data-science tooling you were paying a second vendor for.
Legal billing from Azure SQL.
Time-entry and unbilled reporting off a synced Azure SQL database; PACER invoices allocated billable and non-billable. In use at an AmLaw 100 firm.
What customers say
“Lets us get a lot more out of our data than [...] We can sit on top of all of the data in [our data warehouse] as opposed to just, like, our little ingested, you know, three gigabytes semantic models. I think we have a lot of power here.”
“This is super cool. So in the future, our data will be sitting in [a cloud data warehouse]... How is this running so quickly?”
“It's good to understand the capability of the platform. That how far, and how quickly you guys can get these things going [...] that has been impressive overall.”
“Gave Athena the spreadsheet, explained which column I was trying to figure out, and then ten secs it told me... exactly how the calculation was based on the other data.”
“He wrote the entire stuff. By itself. And I was there, and I was thinking, alright. If I had to write all this stuff, I mean, I would've spent days, days, days.”
“I send that to the programmer and he said, alright. I read your file. I copied the section of the code because he has the right interface, and it works. Wow. Just like magic.”
“One workspace. All different, let's say, avatars of their output data. Right? Suddenly, it's dashboard. Excel is here. PowerPoint is when it's all together. It's very impressive.”
“Use the Athena platform probably closer to the concept and how it was designed, like, with the spaces architecture where you've got a set of primitives and capabilities, and you bring together the right set of capabilities to solve a task.”
“Digital worker, it gets spun up, it gets given access to the toolkits that it needs. It gets given access to the data that it needs. Just exists for the period it needs to exist to perform the task. And then it gets torn back down again afterwards.”
“I like that direction, that concept of the agent is the agent. It becomes an entity in its own right with its own ownership and its own missioning, and you get rid of the gray area and the blurry lines.”
Verbatim from customer calls. Customers anonymized.
Governance
Credentials, permissions, and what to plan for
Each user connects with their own credentials; agents inherit them.
Database assets inherit workspace permissions: owner controls access, versions are tracked.
Results carry a citation to the query and the source.
Deploy with the platform: managed cloud, your VPC, on-prem, air-gapped.
What to plan for
Type inference is good, not perfect. Check the date and ID columns once after a drop; the agent flags the ambiguous ones.
FAQ
What does it give us?
One place for people and agents to query all of your data, without copying it.
Can non-technical people use it?
Yes. They ask in plain language and see the query behind the answer.
Are permissions respected?
Yes. Every query runs with the user's own access.
One platform underneath
AGS · Athena Governance System
Records every change by a person or an agent, rolls back one contributor's edits without losing anyone else's, and keeps the model, instructions, and sources behind each agent action.
Palladium · deployment
How the platform is deployed: Athena's managed cloud, your cloud on AWS, GCP, or Azure, on-prem, air-gapped, or GovCloud. Same platform in every option.
How it fits together
Build, Work, and Data on top; 150+ connectors and every surface in and out; one map of the whole platform.
The rest of the platform
Related products and stories
Bring the CSV that breaks Excel.
We will make it a database, ask it a question, and send the answer to a sheet.