Convert Apache Parquet files (.parquet) to readable JSON locally - each row as an object, nested fields preserved, no upload.
Running locally on your device ...
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Your files never left your device
No. Everything runs in your browser - your file never leaves your device. How this is verifiable
Apache Parquet is the widely used column-oriented binary format for analytical data (Spark, pandas, DuckDB, data lakes). A .parquet file carries its schema and the compressed columns inside it and is very compact - but not readable in an editor. This tool decodes the content and outputs a clear JSON array: one object per data row, with the column names as keys. Unlike CSV, nested fields (lists, structs) stay as a real JSON structure.
Everything runs entirely locally in your browser (hyparquet, pure JavaScript, no upload, even offline). The tool reads the Parquet footer including the schema and decodes the column pages; the page codecs Snappy, Gzip, Zstd, Brotli and LZ4 are supported. For clean values we emit 64-bit integers beyond the safe JavaScript range as a string, timestamps as ISO 8601 text and raw binary values as base64, so no precision is lost.
You need this when a data pipeline, a Kafka export or an analytics job produced a .parquet file and you want to view it, feed it into a tool that speaks JSON (an API, a script, a test), or keep the nested structure. Note: the conversion is one-way (Parquet to JSON); it does not serialize back to Parquet, and logical types such as decimal appear as their underlying base value.
| Input formats | PARQUET |
|---|---|
| Output format | JSON |
| Batch processing | Yes |
| Processing | Locally in your browser (WebAssembly) |
| File upload | None |
Limitations: Parquet files with the codecs Snappy, Gzip, Zstd, Brotli and LZ4 are supported. Encrypted Parquet files are not read. Large 64-bit integers appear as a string (precision), timestamps as ISO 8601, binary values as base64, logical types as their base value. The conversion is one-way (no JSON back to Parquet). Very large files need memory accordingly.
A compact, column-oriented binary format from the analytics world (Spark, pandas, DuckDB). Schema and compression live inside the file.
No. The conversion happens entirely locally in the browser - even offline.
JSON keeps nested fields as a structure and suits code and APIs; CSV is a flat table for spreadsheets.
64-bit integers beyond the safe JS range are output as a string, timestamps as ISO 8601, binary values as base64.
Not here - this tool is one-way (Parquet to JSON) for inspecting and reusing the data.