🚀 Meet Data Porter: My AI-Built Service for Heavy Data Exports

If you’re building for fintech or any system that requires users to download heavy data (transactions, reports, logs), you already know the struggle:

• Queries timeout when datasets grow into millions of rows.

• Users keep downloading the same reports, wasting compute.

• Teams lack audit trails of what was exported, when, and by whom.

I wanted a solution that was scalable, auditable, and secure. So I turned to AI.

In less than 2 hours, I built Data Porter — an open-source service that solves heavy data exports once and for all.

👉 Repo: noibilism/data-export-service

💡 Why Data Porter

The name says it all: Data Porter is the service that “carries” your data safely from your database to a CSV file in S3, ready for download.

It’s built with the realities of fintech in mind:

• Async exports (no API timeouts).

• Deduplication (don’t regenerate the same date-range report twice).

• Audit-ready metadata in its own database.

• Secure S3 presigned URLs so files are accessible only when and where they should be.

⚙️ How It Works

• POST /export → Initiate an export or reuse an existing one if available.

• GET /export/{reference_id} → Check status and get a presigned S3 download link.

Under the hood:

• Streams millions of rows from your transactions database.

• Writes incrementally to CSV (no memory blowups).

• Uploads to S3 with multipart handling for huge files.

• Tracks every job in an Export Service DB.

🛡️ Built for Scale & Security

• Handles 10M+ rows without breaking.

• 5M rows exported in under 15 minutes.

• JWT-authenticated API endpoints.

• Presigned S3 URLs that expire (default: 24h).

🛠️ Built With AI, Fast

This is the part I’m most excited about:
I didn’t spend weeks writing boilerplate or re-inventing patterns. I leveraged AI to design, scaffold, and document the entire service in under 2 hours.

That’s a powerful message for anyone building in fintech: the tooling to deliver production-grade infrastructure quickly is already here.

🚀 Getting Started

The repo includes a Docker Compose setup with API, Worker, Redis, and Postgres.

git clone https://github.com/noibilism/data-export-service.git

cd data-export-service

cp .env.example .env

docker-compose up --build

alembic upgrade head

And you’re ready to start exporting 🚀

🔮 What’s Next

I’m already thinking of where to take Data Porter next:

• Supporting Excel, JSON, Parquet formats.

• Advanced filters (account IDs, transaction types).

• Automatic archival of old exports.

• Role-based access controls.

📌 Final Thoughts

Fintech and data-heavy platforms need exports that don’t break under scale. Data Porter is my attempt to solve this once, cleanly — and the fact that it was built with AI in a couple of hours proves how fast we can move today.

Check it out here: GitHub – noibilism/data-export-service

I’d love to hear how you’d use it in your stack. 🚀