A managed extraction engine that runs on a 256 MB worker — and every number is measured, not projected. → 1 billion rows in one endurance run (99.8% success) → 3.7x faster than Airbyte on identical 1.5M-row sync to BigQuery → 12x less memory · 6x less CPU → Configured by clicking, not by writing SQL or YAML Point ApiTap at an API or database — it lands in your warehouse, typed and deduped. 8 sources, 4 warehouses, free dedicated worker. No credit card.
No reviews yetBe the first to leave a review for ApiTap
Maker
📌
Hey Product Hunt 👋
A few years ago I got hit with a $1,000 Airbyte bill in a single
month — just for moving 100GB of data. At $10/GB, every "let me
sync this new source" suddenly became a business decision instead
of an engineering one.
That month is what made me start building ApiTap.
What it is:
A managed extraction engine that streams APIs and databases to
your warehouse. Configured by clicking — no SQL, no YAML, no
glue code.
What's different:
Built with Rust + Apache DataFusion. Every number on our landing
is measured, not projected:
→ 1 BILLION rows in one endurance run (99.8% success)
→ 3.7x faster than Airbyte on identical 1.5M-row sync to BigQuery
→ 12x less memory · 6x less CPU
→ Runs on a single 256 MB dedicated worker
What's live today:
- Sources: GitHub, Stripe, Salesforce, Jira, Shopify, HubSpot,
Postgres, MySQL
- Warehouses: Postgres, BigQuery, ClickHouse, Snowflake
- S3 coming soon
Free dedicated worker to start — no credit card.
I'd love your honest feedback on:
1. Is "configured by clicking" believable, or sounds too good?
2. Which source connector should I build next?
3. What's the one thing that would make you NOT trust this for
production data?
Solo founder, building in public. Will be here all day answering
questions — happy to dive into the architecture, the benchmarks,
or the journey.
Thanks for checking it out 🙏