1
Duckle is an open-source desktop ETL/ELT studio that enables users to easily create data pipelines. Users can simply drag a pipeline onto the canvas, describe their requirements in plain English to Duckie, the on-device AI assistant, and execute tasks at native speed using DuckDB.
Key features include: - 290+ connectors - 50+ transforms - A built-in scheduler - A chat assistant that operates entirely on your CPU - 60 UI Languages - Git Integration
Duckle is delivered as a compact ~30 MB desktop application, ensuring no reliance on cloud services, servers, or vendor lock-in.
Explore the repository here: https://github.com/SouravRoy-ETL/duckle/
Code - https://github.com/SouravRoy-ETL/slothdb
https://github.com/SouravRoy-ETL/slothdb
Looking for contributors who can bring my personal experimental project to life with ideas, suggestions issues etc. This is not a job posting but I am looking for fellow open source contributors.
Repo Link for all Details on the project! https://github.com/SouravRoy-ETL/slothdb
Point any SQL at any file. Parquet, CSV, JSON, Avro, Arrow, SQLite, Excel. No server, no import step, no extension to install before you can read a Parquet file. Same embedded model as SQLite and DuckDB, different defaults.
A few things we cared about while building it: It is one binary. Drop slothdb.exe somewhere, run it. It also runs in the browser. The WASM build is 1.3 MB and fits Workers 1 MB script cap in the edge variant.
It is fast enough to be worth the swap for analytical work. On a 5 query warm batch over 10M rows, SlothDB finishes in 138 ms. DuckDB 1.1.5 finishes the same batch on the same hardware in 540 ms.
It is also early and in development stages. v0.2.0. The Python wheel had a packaging bug that was only caught because a stranger filed an issue. So if you hit a rough edge, file one. SlothDB reads every one them.