Thunderduck is a DuckDB-powered data warehouse built for AI agents. Every agent gets its own isolated engine. Join Postgres, BigQuery, Iceberg and S3 files in one SQL query, with no ETL. Every query is priced before it runs. Managed cloud, BYOC or on-prem.
We've built data platforms for years, and the first six months always went to the same thing: moving data from where it already lived into a warehouse that charged us rent for keeping it. Meanwhile DuckDB answered the same questions in seconds, on a laptop.
Now AI agents are joining data teams, and they make this worse. An agent will happily scan 400 GB to answer a simple question, because it never sees the bill.
So we built Thunderduck: a modular data warehouse on DuckDB, designed for humans and agents working side by side.
🦆 One engine per agent. Each agent or user gets its own isolated engine, sized to the query. No shared cluster, no noisy neighbors.
🔗 Query in place. Join Postgres, MySQL, BigQuery, ClickHouse, Iceberg, and files in S3, GCS, Azure or Cloudflare R2, all in one SQL query. Filters run inside each source.
💸 Guardrails. Every query gets a cost and runtime estimate before it runs, and access is scoped per person and per catalog.
🤖 Bring your own AI. Connect Claude, ChatGPT or Cursor over MCP. Agents find the right table, understand what the columns mean, and build dbt pipelines on a branch for your review.
☁️ Run it anywhere. Our cloud, your AWS or GCP account, or on-premise.
A cost estimate before the query runs gives the agent something concrete to work with. Keeping that estimate beside the actual cost would help the team spot which queries need a closer look.
About Thunderduck Inc. on Product Hunt
“Modular Data Warehouse for Agentic Data Teams”
Thunderduck Inc. launched on Product Hunt on November 6th, 2026 and earned 73 upvotes and 2 comments, placing #27 on the daily leaderboard. Thunderduck is a DuckDB-powered data warehouse built for AI agents. Every agent gets its own isolated engine. Join Postgres, BigQuery, Iceberg and S3 files in one SQL query, with no ETL. Every query is priced before it runs. Managed cloud, BYOC or on-prem.
Thunderduck Inc. was featured in Developer Tools (522.6k followers), Artificial Intelligence (483k followers) and Data & Analytics (6k followers) on Product Hunt. Together, these topics include over 231.9k products, making this a competitive space to launch in.
Who hunted Thunderduck Inc.?
Thunderduck Inc. was hunted by Yildirim Adiguzel. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Thunderduck Inc. stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Yildirim Adiguzel
Hey Product Hunt 👋
We've built data platforms for years, and the first six months always went to the same thing: moving data from where it already lived into a warehouse that charged us rent for keeping it. Meanwhile DuckDB answered the same questions in seconds, on a laptop.
Now AI agents are joining data teams, and they make this worse. An agent will happily scan 400 GB to answer a simple question, because it never sees the bill.
So we built Thunderduck: a modular data warehouse on DuckDB, designed for humans and agents working side by side.
🦆 One engine per agent. Each agent or user gets its own isolated engine, sized to the query. No shared cluster, no noisy neighbors.
🔗 Query in place. Join Postgres, MySQL, BigQuery, ClickHouse, Iceberg, and files in S3, GCS, Azure or Cloudflare R2, all in one SQL query. Filters run inside each source.
💸 Guardrails. Every query gets a cost and runtime estimate before it runs, and access is scoped per person and per catalog.
🤖 Bring your own AI. Connect Claude, ChatGPT or Cursor over MCP. Agents find the right table, understand what the columns mean, and build dbt pipelines on a branch for your review.
☁️ Run it anywhere. Our cloud, your AWS or GCP account, or on-premise.
The first 2 query-hours each month are free.