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File SQL
Query local & S3 files with SQL — inside VS Code.
Every analyst has stared at a folder of Parquet or CSV files and thought: "I just want to SQL this." File SQL does exactly that — inside VS Code. Drop in a file path, an S3 URI, or a whole folder. Each subfolder becomes a table. Query it with DuckDB. Done. Why it stands out: Local files and S3 — one extension, one workflow, Right-click any file in Explorer → instant SQL table, Multi-tab query editor with autocomplete, Runs entirely on your machine
Hey I'm Arunkumar
I built File SQL because I kept doing the same annoying thing at work: someone would send me a Parquet file or an S3 path, and I'd spin up a Jupyter notebook just to peek inside it. Six lines of pandas boilerplate later I'd forgotten what I was even looking for.
So — right-click a file in VS Code, get a SQL table. That was the whole idea.
It works on CSV, JSON, Parquet, TSV, and a few others. If you point it at a folder (local or S3), each subfolder becomes its own table, which turned out to be really handy for partitioned datasets. Under the hood it's DuckDB, so queries on a few million rows feel instant on a laptop.
A few things I care about:
- Local files and S3 both work the same way. Most tools pick one.
- Nothing leaves your machine. No accounts, no telemetry, no cloud backend.
- Free and MIT- licensed. I use it every day myself.
I'd love to hear:
- Any feature that would make it a daily-driver for you?
- Bugs — please break it and tell me how 🙏
About File SQL on Product Hunt
“Query local & S3 files with SQL — inside VS Code.”
File SQL was submitted on Product Hunt and earned 7 upvotes and 11 comments, placing #96 on the daily leaderboard. Every analyst has stared at a folder of Parquet or CSV files and thought: "I just want to SQL this." File SQL does exactly that — inside VS Code. Drop in a file path, an S3 URI, or a whole folder. Each subfolder becomes a table. Query it with DuckDB. Done. Why it stands out: Local files and S3 — one extension, one workflow, Right-click any file in Explorer → instant SQL table, Multi-tab query editor with autocomplete, Runs entirely on your machine
On the analytics side, File SQL competes within Analytics, GitHub, Data & Analytics and Database — topics that collectively have 222k followers on Product Hunt. The dashboard above tracks how File SQL performed against the three products that launched closest to it on the same day.
Who hunted File SQL?
File SQL was hunted by Arunkumar Bhat. 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.
For a complete overview of File SQL including community comment highlights and product details, visit the product overview.
Arunkumar Bhat