JA Technology Solutions
Parquet File Explorer
View and explore Apache Parquet files entirely in your browser. See schema and metadata, browse data with filtering, export to CSV/JSON/Excel, or convert files to Parquet.
Parquet File Explorer
Open Apache Parquet files directly in your browser with three views: Schema (column names, physical and logical types, compression codecs, row groups, file metadata — see how data is organized across row groups), Data (tabular view with per-column text filters, click-to-sort headers, and virtual scrolling that handles large files without slowing the browser down), and Convert (export loaded Parquet to CSV, JSON, or Excel with active column filters carried through, or drop a CSV, JSON, or Excel file to convert it to Parquet format with automatic type inference and preview before download). All processing happens client-side — your data never leaves your browser.
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What Is Apache Parquet?
Apache Parquet is an open-source columnar storage format designed for efficient data processing at scale. Unlike row-based formats like CSV or JSON where each line stores all fields for one record, Parquet stores values column by column. This columnar layout enables dramatic compression ratios because similar values (all the dates, all the prices, all the status codes) sit next to each other and compress well together. It also means analytical queries that touch only a few columns can skip the rest entirely, reading a fraction of the file.
When to Use Parquet
Parquet shines in data lakes, analytics pipelines, and any scenario where data is written once and read many times with selective column access. Tools like Apache Spark, AWS Athena, Google BigQuery, DuckDB, Pandas, and Polars all read Parquet natively. If you are exporting data for analytical consumption, Parquet is almost always a better choice than CSV — files are smaller, reads are faster, and the schema (column names and types) is embedded in the file rather than guessed by the consumer. CSV remains the better choice for interchange with legacy systems, spreadsheets, and human-readable quick checks.
Building Data Pipelines with Parquet
This tool handles one-off exploration and conversion. For production pipelines — scheduled extracts from databases to Parquet, format conversion stages in ETL workflows, or Parquet-to-warehouse ingestion — I build custom solutions that handle schema evolution, partitioning, compression tuning, and delivery to cloud storage or analytics platforms. Learn about ETL services, explore data integration, or get in touch to discuss your data pipeline.
All tools run entirely in your browser. Your data never leaves your machine. Need help? Ask James.