For the past couple of weeks, I've been co-working on SlothDB - an open-source embedded analytical database engine in C++20. Think DuckDB, but with some things I always wished DuckDB had.
Why I chose to work on it:
Every time I used DuckDB in real life, I hit the same 3 problems:
→ Extensions broke on every upgrade
→ Error handling was impossible (free-form strings, no codes)
→ No GPU acceleration for large-scale analytics
So I cowrote my own. From scratch. Zero external dependencies.
What SlothDB does differently:
1. GPU Acceleration (CUDA + Metal) — 20-100x faster on datasets with 100K+ rows. Your M1 Mac can now crunch analytics on the GPU.
2. Extensions never break — Stable C ABI. An extension built for v1.0 works on v2.0. No more "please rebuild all extensions after upgrading."
3. Structured error codes — Every error has a numeric code that's stable across versions. Write error handling once, never fix it again.
4. 7 file formats built-in — CSV, Parquet, JSON, Arrow, Avro, Excel, SQLite. No extensions to install. Just: SELECT * FROM 'report.xlsx'
5. QUALIFY clause — Snowflake's best feature. Filter window functions without subqueries.
By the numbers:
- 130+ SQL features
- 325 tests, 131,000+ assertions
- Zero external dependencies
- Single-file persistence (.slothdb)
- Runs on Windows, Linux, macOS
Try it in 10 seconds:
GitHub: https://github.com/SouravRoy-ETL...
The hardest part wasn't the SQL parser or the vectorized execution engine. It was making the file format readers work cross-platform with zero dependencies. Parsing
Parquet files without Apache Arrow? That was fun.
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About SlothDB on Product Hunt
“Embedded analytical database engine built in C++”
SlothDB was submitted on Product Hunt and earned 1 upvotes and 1 comments, placing #133 on the daily leaderboard. An embedded analytical database engine built in C++20. Zero dependencies. GPU accelerated (CUDA + Metal). 130+ SQL features. Query CSV, Parquet, JSON, Excel directly. DuckDB alternative with QUALIFY, structured errors, and stable extension API. - SouravRoy-ETL/slothdb
SlothDB was featured in GitHub (41.2k followers), Tech (621.5k followers), Data & Analytics (5.5k followers) and Database (2.1k followers) on Product Hunt. Together, these topics include over 184.7k products, making this a competitive space to launch in.
Who hunted SlothDB?
SlothDB was hunted by Sourav Roy. 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 SlothDB stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sourav Roy