Parquet & Arrow In-Browser SQL Studio – Columnar Query Engine
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In-Browser Columnar Storage Analytics & Parquet Inspection
Apache Parquet has become the de-facto storage format for modern data lakes (Databricks, Snowflake, BigQuery, AWS Athena). Inspecting Parquet files locally traditionally required heavy Python environments with PyArrow or Pandas. This tool parses binary Parquet metadata and dictionary encodings right in browser memory.
Zero-Egress Security for Sensitive Datasets
Big data files often contain confidential business transactions, customer PII, or internal telemetry. Because processing runs entirely client-side, zero rows or columns are ever transmitted over the network.
Frequently asked questions
What Parquet compression types are supported?
Standard uncompressed and dictionary-encoded binary Parquet archives are parsed directly via ArrayBuffer DataView.
Can I query large multi-megabyte files?
Files under 100MB are supported smoothly in modern browsers with zero external infrastructure overhead.
Query petabyte datasets with instant autoscaling and zero infrastructure maintenance.