$1,000 Airbyte bill made me build this — sharing pre-launch

Hey makers 👋

Pre-launch sharing because this is the right forum for it.

A few years ago I got hit with a $1,000 Airbyte bill in one month —

just for moving ~100GB of data. Looked at Fivetran (pricing got even

scarier at scale) and dlt (great but Python-only for everything).

So I built ApiTap: a managed extraction engine that runs on a

256 MB worker. Rust + Apache DataFusion under the hood.

Every number on apitap.dev 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 — no SQL, no YAML, no glue code

What's live today:

- Sources: GitHub, Stripe, Salesforce, Jira, Shopify, HubSpot,

Postgres, MySQL

- Warehouses: Postgres, BigQuery, ClickHouse, Snowflake

Free dedicated worker, no credit card → https://apitap.dev/

Pre-launch, so brutal feedback > polite encouragement:

1. Is "managed + lightweight + click-only" a real wedge, or am I

solving for yesterday's problem?

2. Which source connector should I prioritize next?

3. What's the one thing that would make you NOT trust this for

production data?

Solo founder, building in public. Thanks for checking it out 🙏