GoKawiilDeveloper shows Parquet cube + range requests can replace a database for dashboards
A blogger built a customer analytics drilldown dashboard using only a 40MB pre-aggregated Parquet 'data cube' stored in R2, an 18KB browser-based Hyparquet reader, and HTTP range requests, avoiding any database or query engine. The demo rolled up NYC's 34-million-row 311 service request dataset into a compact cube that supports fast filtering by reading only small slices of the file at a time.
GoKawiil's interpretation of the reporting above, not reported fact.
This approach challenges the assumption that customer-facing analytics dashboards require a hosted database or query engine like DuckDB's cloud offerings, potentially cutting infrastructure costs and vendor dependencies for simple use cases. It highlights how much of the complexity in analytics products actually lives in the data pipeline that builds these pre-aggregated files, not in query serving itself.
- A 40MB Parquet cube plus an 18KB JS reader can power interactive dashboards without a database.
- The technique relies on HTTP range requests against object storage like Cloudflare R2 to fetch only needed data slices.
- The real engineering effort shifts to building the pipeline that produces well-structured, pre-aggregated Parquet cubes.
O'Reilly "DuckDB: Up and Running" by Wei-Meng Lee — If this post's Parquet-on-object-storage tricks sparked ideas, this book walks you through DuckDB's analytical SQL engine, including querying Parquet files directly. It's a practical companion for anyone building lightweight dashboards without spinning up a data warehouse.
See O'Reilly "DuckDB: Up and Running" by Wei-Meng Lee on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: hamiltonulmer.com, 2026-08-24
Published there as: “Fast drilldown dashboards from a single Parquet file”
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