- How do I convert JSON to CSV?
- Paste your JSON array of objects into the input field. The tool automatically generates CSV with column headers from JSON keys. Download the .csv file or copy the text to clipboard.
- Can this handle nested JSON objects?
- Yes. Nested objects are flattened using dot notation — for example, {user: {name: 'John'}} becomes a column named 'user.name' with value 'John'.
- Can I open the CSV output in Excel or Google Sheets?
- Yes. Download the .csv file and open it directly in Excel, Google Sheets, LibreOffice Calc, or any spreadsheet application.
- Is my JSON data uploaded to a server?
- No. All conversion runs locally in your browser. No data is sent to any server — this makes it safe for sensitive or proprietary data.
- What JSON format does this converter expect?
- The converter works best with JSON arrays of objects, like [{"name":"John","age":30},{"name":"Jane","age":25}]. Each object becomes a CSV row, and keys become column headers.
- Is this JSON to CSV converter free?
- Yes — 100% free, no signup, no rate limit, no size limit. Unlike some tools that gate features behind paid tiers or require sign-in for large files, every feature here is unlimited and free forever.
- How do I open the CSV in Excel without garbled characters?
- Enable the UTF-8 BOM checkbox before downloading. Excel on Windows requires the BOM to correctly detect UTF-8 encoding — without it, accented characters and emoji appear as 'é' or '?'. The BOM is a 3-byte marker (EF BB BF) at the start of the file that tells Excel 'this is UTF-8'. For European locales, also use semicolon delimiter instead of comma.
- Can I convert JSON with thousands of rows?
- Yes — easily. The tool handles JSON files with hundreds of thousands of rows. Processing is client-side so the constraint is browser memory, typically allowing files up to ~50-100 MB on a modern machine. For larger datasets, split into chunks or use a CLI tool like jq + csvkit.
- What if my JSON objects have different keys?
- The converter scans ALL objects and builds a union of every unique key as columns. Missing values produce empty cells (or whatever you set as the 'null handling' option). This handles inconsistent JSON (common from MongoDB or NoSQL exports) gracefully — every row gets every column, just with empty values where the source didn't have that key.
- Can I convert nested JSON to CSV?
- Yes. Nested objects are flattened with dot notation: `{user: {name: 'Alice'}}` becomes column `user.name` with value `Alice`. Deeply nested structures (3+ levels) flatten the same way: `user.address.city`. Arrays inside objects are joined with a configurable separator (pipe, comma, or JSON-stringified for preservation).
- Will this work for BigQuery / Snowflake / Redshift COPY?
- Yes — the output is RFC 4180-compliant CSV that all major data warehouses accept. Use comma delimiter, disable BOM (data warehouses don't need it and may interpret it as data), and ensure NULL handling matches your target (BigQuery wants empty for NULL, Snowflake accepts both empty and the literal 'NULL').
- Is my JSON data uploaded anywhere?
- No. All conversion runs locally in your browser. Your JSON data — including any tokens, PII, or business-sensitive content — never reaches any server. Safe for proprietary data. Verify by opening DevTools → Network tab while converting: zero outgoing requests.
