DataForge — Distributed ETL pipeline engine built on Go The free, open ETL engine that handles data at scale — no setup hell. What it does ? -> Upload CSV → Analyze → Clean → Normalize → Deduplicate → Export Focused on: -> Go concurrency patterns -> Worker pool architecture -> Priority-based job dispatching -> Real-world ETL pipeline design

Tines — Build agents & automations integrated across your workspace

Build agents & automations integrated across your workspace

With DataForge, you can import raw data, clean it, normalize it, and deduplicate it at scale — all from a single, fast, and intuitive interface. No vendor lock-in. No credit card. No nonsense. The Problem I Saw: When I started working with real-world datasets during my B.Tech engineering coursework, I hit the same wall every developer hits: the tools that handle large-scale ETL are either too expensive, too complex, or both. Apache NiFi, Talend, AWS Glue — powerful, yes. But for a student, a startup, or a solo developer, these tools come with steep learning curves, enterprise pricing, and heavyweight infrastructure. On the other end, manual scripts break the moment your dataset scales. There was nothing in the middle — a free, scalable, developer-first ETL engine that just works. So I built one.

Tines — Build agents & automations integrated across your workspace

Build agents & automations integrated across your workspace

DataForge

Distributed ETL pipeline engine.

Distributed ETL pipeline engine.