Rows and columns
CSV and XLSX are familiar tabular formats, while JSON and JSONL can represent records differently. Conversion maps available source fields into the destination model.
Convert Parquet, CSV, JSON, JSONL/NDJSON, Avro, ORC, Arrow and Feather in one Data Studio. Available outputs depend on the source and include CSV, JSON, JSONL, Parquet and XLSX.
Drag and drop, paste a file, or browse your device.
Files are temporary and deleted automatically.
Use MimiFile's data workspace when the source is structured data rather than a document meant primarily for visual layout. Supported routes include text-based interchange formats, spreadsheets and columnar or analytics-oriented formats.
CSV and XLSX are familiar tabular formats, while JSON and JSONL can represent records differently. Conversion maps available source fields into the destination model.
Parquet, ORC and Arrow are designed for data-processing workflows and do not behave like visual spreadsheet documents.
Data types, nested structures, null values and column names may have different representations across formats, so validate important datasets after conversion.
No. CSV is delimited text, while Parquet is a typed columnar format; a real conversion writes the destination data structure.
No. Nested objects and arrays do not always map one-to-one to rows and columns, so the result should be reviewed.
Yes, especially when dates, numbers, nulls, nested fields or schema-sensitive analytics workflows are involved.