About

Data portability is the cornerstone of modern backend engineering. While JSON (JavaScript Object Notation) is the de facto standard for API responses due to its ability to handle nested hierarchies and variable schemas, it is often incompatible with the tabular nature of business intelligence tools, SQL databases, and Excel. This misalignment creates a critical "Data Friction" point.

This tool acts as a high-fidelity ETL (Extract, Transform, Load) layer running entirely in your browser. Unlike basic converters that discard nested objects or choke on irregular arrays, this engine employs a Recursive Flattening Algorithm. It traverses the depth of the JSON tree (d) to generate dot-notation headers (e.g., user.profile.settings.theme), ensuring zero data loss. It is specifically architected to handle "Sparse Data" - datasets where keys exist in some records but not others - by performing a full-pass schema discovery before generation.

Security and Privacy are paramount. All processing occurs client-side within the JavaScript Sandbox. No data is ever sent to a server, making this safe for sensitive PII, financial logs, or proprietary configurations.

Formulas

The core complexity of flattening a JSON tree can be modeled as a depth-first traversal where the resulting column set C is the union of all keys across all records R.

C = N∪i=1 keys(flatten(r_i))

Where the flattening function follows the recursive definition:

{

flatten(v, k.sub_k) if v ∈ Objectk : v otherwise

For a dataset of size S bytes with nesting depth D, the time complexity approaches O(S × D). To prevent UI blocking, we partition the iteration into chunks of 50ms execution time.

Reference Data

Feature	Standard Converters	This Enterprise Tool
Nested Objects	Often ignored or returns [Object]	Recursive flattening (parent.child)
Schema Detection	First row only	Union of ALL rows (∪ K)
Array Handling	Fails or Errors	Configurable: Join, Stringify, or Spread
Large Files	Browser Crash (OOM)	Chunked Processing (Async Event Loop)
Data Types	Everything is String	Preserves Number, Boolean, Null
Formatting	Basic Comma	Custom Delimiters (; \| \t) & RFC 4180
Privacy	Server-side (Risk)	100% Client-side (Safe)

Frequently Asked Questions

A sparse schema occurs when objects in an array have different keys (e.g., Record A has "email", Record B has 'phone'). Our engine performs a pre-scan of the entire dataset to build a "Master Header List". If a record lacks a specific key, the resulting CSV cell is left empty (or filled with a custom default), ensuring perfect column alignment.

Excel often aggressively auto-formats large numbers (like Credit Card numbers or Database IDs) into scientific notation (e.g., 1.23E+10). To prevent this, simple CSVs are insufficient. While standard CSV doesn't support types, you can use our "Force Text" option to wrap numbers in quotes and an equals sign (="123") which forces Excel to treat them as literals.

Yes. While browser memory limits exist (typically ~2GB tab limit), our tool uses "Chunked Processing". It breaks the work into small tasks, allowing the UI to remain responsive. However, extremely large files (500MB+) are recommended to be processed via command-line tools to avoid browser crashing, though our tool pushes the limit of what's possible in the DOM.

Arrays pose a challenge for flat formats. We offer two modes: 1) "Stringify" (default) converts the array `[1,2]` into the string "[1,2]". 2) "Join" converts it to "1|2". We do not currently "explode" arrays into new rows as this multiplies the dataset size exponentially, which can crash the browser.

Absolutely not. This tool is a "Client-Side Single Page Application". The code runs entirely within your browser's memory. You can verify this by disconnecting your internet after the page loads; the tool will still function perfectly.