Open 10+ GB JSON, XML & CSV in a blink.
A zero-copy, memory-mapped viewer that opens, navigates and regex-searches enormous data files without ever loading them into memory — 10+ GB on a laptop, and 50+ GB on a 32–64 GB machine. Performance scales with your RAM.
1{ 2 "events": [ 3 { "id": 8842013, "level": "error", 4 "service": "checkout" }, 5 { "id": 8842014, "level": "info" } 6 ] 7}
// a developer, to a developer
Built by a developer who lives in big data — for the ones who do too.
No bloat, no telemetry, no progress bars — just the tool we wished existed every time an editor choked on our files.
One viewer for every large data format
Open it. Navigate it. Find anything.
Every file is memory-mapped and parsed once into a compact index — only the rows on screen are ever built.
Open the file
Drag in a JSON, NDJSON, XML, CSV or TSV file up to 10+ GB (50+ GB with 32–64 GB of RAM) — or paste from the clipboard or fetch a URL with auth. It opens instantly, no progress bars.
Navigate the tree
Everything renders as one uniform, virtualized tree. Jump to any path, bookmark nodes, and read collapsed counts like “products : […], 31 items”.
Search & export
Regex find, live filter, or JSONPath / XPath queries backed by parallel native search. Then export or convert to JSON, XML or CSV.
Built for scale, byte by byte.
A native engine treats your data as structure, not text — so memory tracks your working set, not the file size.
The result speaks for itself.
Approximate load time for a large JSON file. Where general-purpose editors stall or run out of memory, the structural index just opens.
Illustrative comparison on a large JSON file. Actual results vary by hardware, file shape and configuration.
A data workbench, not a text editor.
Browse and query your files like a database — with the tools you'd expect from an enterprise DBMS.
Virtualized tree view
Objects, arrays, XML elements and CSV records render in one uniform, collapsible tree. Cost per frame tracks visible rows (~40), never file size.
Regex find, instantly
Literal or regex search scoped to keys, values or attributes — chip-highlighted matches with ▲▼ stepping, backed by parallel native search.
JSONPath & XPath queries
Query JSON/CSV with $.store.items[*].name and XML with //item/@id. Combine paths to pull several fields at once; results filter the tree.
On-demand (lazy) indexing
Files too large to index eagerly open anyway — only the paths you expand are materialized, so resident memory tracks the subtree you view.
CSV spreadsheet view
CSV/TSV opens in a grid with header detection. Leading-zero cells like ZIP codes deliberately stay strings — no silent data loss.
Follow tail (tail -f)
Follow a growing JSON / NDJSON / log file. Only newly appended lines are parsed each tick, so it stays cheap on huge, live files.
Convert & export
Export the whole document or any node as pretty JSON, XML or CSV — cross-format conversion built in, plus export of search matches.
Open from URL
Fetch a document over HTTP(S) with None / Basic / Bearer / API-Key auth, remember credentials, and copy the request as cURL.
Node statistics
Right-click any container for child counts, a type histogram, distinct values and numeric min / max / avg — understand your data fast.
Other tools weren't built for gigabytes.
General-purpose editors treat JSON as plain text. OPENXMLJSON treats it as structured data.
| OPENXMLJSON | Text editors | Browser / online | |
|---|---|---|---|
| Opens 10+ GB files | ✓ | ✕ | ✕ |
| Memory tracks working set, not file size | ✓ | ✕ | ✕ |
| Structural tree navigation | ✓ | ✕ | Limited |
| Parallel regex search | ✓ | Slow | ✕ |
| JSONPath / XPath queries | ✓ | ✕ | ✕ |
| Follow a live / growing file | ✓ | ✕ | ✕ |
| Cross-format convert (JSON/XML/CSV) | ✓ | ✕ | Partial |
| Data never leaves your machine | ✓ | ✓ | ✕ |
What people say.
“Opened an 8 GB NDJSON log that crashed everything else. It was on screen before I finished my coffee.”
“The JSONPath query bar plus regex find replaced three scripts I used to run to inspect API dumps.”
“Follow-tail on a live JSON log is the feature I didn't know I needed. Memory just doesn't move.”
What to know before you download.
How large a file can it really open?
On a typical machine it's comfortable around 10 GB. With 32–64 GB of RAM it opens 50+ GB files — performance scales with the memory you give it. Files too large to index eagerly fall back to on-demand (lazy) indexing, so documents near or beyond your available RAM still open.
Which formats are supported?
JSON, JSON-Lines / NDJSON, XML, CSV and TSV. The parser is chosen from the file extension, and you can also paste from the clipboard or open from a URL.
Does my data leave my machine?
No. Files are memory-mapped and processed locally. Nothing is uploaded — the only network call is the optional Open-URL fetch you trigger yourself.
What platforms does it run on?
Windows, macOS (universal, Apple Silicon + Intel) and Linux.
What's the difference between Essential and Premium editions?
They're the same complete app with no file-size limit — the only difference is billing: Essential is monthly and Premium is yearly. NARIKJSON is our top-tier edition, above Premium — adding volume licensing, managed deployment and an SLA. Want to try first? The free download opens files up to 50 MB.
Stop waiting on progress bars.
Download OPENXMLJSON and open your biggest file in seconds.