Developer Guide
JSON to CSV: Data Migration Patterns That Work
Flatten nested JSON, handle arrays, choose the right delimiter, and avoid encoding pitfalls in data migration pipelines.
Flattening Strategies for Nested JSON
JSON is hierarchical; CSV is flat. The most common flattening strategy uses dot-notation for keys: "address.city" becomes a column header. Arrays are harder — a "phoneNumbers" array with two entries can produce either two rows (repeating parent data) or a single row with a JSON-stringified cell. Our converter offers both modes: "expand" creates one row per array element, "compact" stores arrays as JSON strings in a single cell.
CSV Encoding Pitfalls
CSV has no universal standard. Values containing commas must be quoted with double quotes. Values containing double quotes must escape them as "". Multi-line values must be quoted. Our converter follows RFC 4180: all cells are properly quoted and escaped. For Excel compatibility (especially on non-English systems), use semicolons as delimiters — our tool supports switching between comma, semicolon, and tab delimiters.
Large Dataset Handling
For datasets over 10MB, browser-based CSV conversion may hit memory limits. For production ETL, use a streaming approach with Node.js streams or jq on the command line. Our converter is optimized for moderate datasets (up to 10MB) commonly encountered in data analysis and spreadsheet imports.