How it works
Add your JSON file. MimiFile checks the format, converts it to Apache Parquet, and provides a temporary download when the result is ready.
Convert a JSON object or array of objects to Parquet when you need a typed columnar file for analytics, data pipelines, query engines or compact storage.
JSON → PARQUET
Drag and drop, paste a file, or browse your device.
Files are temporary and deleted automatically.
Limits: 16 MB per file · 128 MB total per batch.
Add your JSON file. MimiFile checks the format, converts it to Apache Parquet, and provides a temporary download when the result is ready.
MimiFile builds an Arrow table from the JSON records, then writes Parquet with Zstandard compression, dictionary encoding and statistics. Check inferred types and nested fields before production use.
Current source limit : 16 MB per file. Up to 10 files can be submitted in a batch, subject to the global batch ceiling.
This route accepts one JSON object or an array of JSON objects. Records must form a compatible table; scalar-only JSON or arrays containing non-object values are rejected.
MimiFile writes a typed Parquet 2.6 file using Zstandard compression, dictionary encoding and column statistics. That makes the result different from simply storing JSON text in another extension.
JSON has no single mandatory tabular schema. Check numeric types, timestamps, nulls, nested values and application-specific assumptions before using the Parquet output in a production pipeline.
When a tabular destination cannot represent lists or objects directly, nested values are serialized as JSON text where supported instead of being silently discarded.
Nulls and timestamps are preserved when the destination supports them. Binary values can be represented as Base64 text in text-based or spreadsheet outputs.
Check column types, null values, timestamps and nested fields before using the converted file in a production data pipeline.