This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Pilotbase
Universal database GUI for SQL, NoSQL, and vector DBs
• One web UI for 19+ database types: PostgreSQL, MySQL, MongoDB, Redis, Qdrant, ChromaDB, Weaviate, and more • Self-host with dockerfile, fully open source (MIT license) — zero vendor lock-in • Built-in AI agent (LangGraph + ReAct) that queries databases in plain English • Works with local Ollama or any OpenAI-compatible LLM • Docker Compose setup in 3 minutes • AI Agent re-uses the connection that is already present in Pilotbase to do SELECT queries on databases when required by user.
How does the AI agent handle schema introspection across the 19+ database types, especially something like Redis or vector stores like Qdrant where the "schema" looks pretty different from a traditional relational DB?
How does the AI agent actually decide when to fall back on plain SQL versus pulling from vector stores like Qdrant or ChromaDB, and can you override that routing logic?
How does the AI agent handle schema discovery across the 19+ database types, and does it keep an internal map of table relationships or query it on the fly each time?
Finally tried Pilotbase with my Postgres and a local Ollama setup, and the docker compose came together in a couple of minutes like advertised. The plain English querying feels surprisingly natural, even on a messy schema.
How does the AI agent handle permissions when querying multiple databases at once, like does it need separate credentials for each one or can you scope access across them from a single config?
About Pilotbase on Product Hunt
“Universal database GUI for SQL, NoSQL, and vector DBs”
Pilotbase was submitted on Product Hunt and earned 3 upvotes and 5 comments, placing #156 on the daily leaderboard. • One web UI for 19+ database types: PostgreSQL, MySQL, MongoDB, Redis, Qdrant, ChromaDB, Weaviate, and more • Self-host with dockerfile, fully open source (MIT license) — zero vendor lock-in • Built-in AI agent (LangGraph + ReAct) that queries databases in plain English • Works with local Ollama or any OpenAI-compatible LLM • Docker Compose setup in 3 minutes • AI Agent re-uses the connection that is already present in Pilotbase to do SELECT queries on databases when required by user.
Pilotbase was featured in Productivity (655.7k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 349.5k products, making this a competitive space to launch in.
Who hunted Pilotbase?
Pilotbase was hunted by Harish Palaniappan. 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.
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Harish Palaniappan
How does the AI agent handle schema introspection across the 19+ database types, especially something like Redis or vector stores like Qdrant where the "schema" looks pretty different from a traditional relational DB?