DatasetDeck
A no-code publishing tool: drag in a Parquet or CSV file and instantly get a paginated, cost-predictable API endpoint that dashboards and partner integrations can query without backend engineering.
Data analysts and BI leads who own large datasets but lack engineering bandwidth to publish them as APIs
- Drag-and-drop Parquet or CSV upload with auto-generated schema documentation and column-level type hints
- Built-in row-range pagination that stays fast up to 100M+ rows using row-group skipping, not naive OFFSET
- Webhook and scheduled-query subscriptions so consumers get notified of new rows or refreshed files
- Cost-per-page calculator and rate-limit dashboard so the data owner can price access and detect abuse
DuckDB-class performance just made it cheap to serve paginated slices of huge files, but the engineering glue to turn a file into an API still requires a backend team; the HN article explicitly demonstrated this gap.
HN post hit 28 points; the underlying problem (returning large files via paginated APIs) is universal for any data team with millions of rows.QuickAPI • Turn your assets into a micro-saas, no-code required ↗
Existing tools (AWS Data Exchange, S3 plus API Gateway) require engineering to assemble; no one ships a drag-and-drop file-to-API for huge datasets.QuickAPI • Turn your assets into a micro-saas, no-code required ↗
Data infrastructure buyers are used to $200-2000 per month pricing; per-page usage fees are a clean upsell.QuickAPI • Turn your assets into a micro-saas, no-code required ↗
Large datasets and partner-data sharing are permanent business needs, not trend-dependent.
DuckDB already handles the hard performance work; the gap is the API shell, schema docs, and subscription plumbing.