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BigJSON
Free, open-source large JSON file viewer Dadroit alternative
Open and search multi-gigabyte (2–3 GB) JSON files on macOS and Windows in seconds. A free, open-source alternative to Dadroit: tree viewer, key & value RegEx search, copy & extract any value or subtree, JSON to CSV/XML export, and multi-file union. No cost, no limits, commercial use free.
Hey Product Hunt 👋
I built BigJSON because opening a big JSON file is somehow still painful in 2026. Every time I had to inspect a 2–3 GB export — API dumps, logs, GeoJSON — VS Code would hang, my browser tab would crash, and "just use jq" isn't much fun when you actually want to browse the data. The native tools that handle this well tend to paywall large files and commercial use, so I built the free, open-source one I wanted.
BigJSON is a native viewer for multi-gigabyte JSON on macOS & Windows. The trick: it never parses the file into memory. It memory-maps the file and builds a compact streaming index (~23 bytes/node), then renders only the rows on screen — so it opens a 2–3 GB JSON in ~3 seconds and searches the whole file instantly, staying around 1.5–2× the file size in RAM instead of ballooning to 20–30 GB.
What it does:
• 🌳 Collapsible, syntax-highlighted tree — browse from root to leaf
• 🔍 Search keys and values — plain or regex, with jump-to-match
• 📤 Export JSON → CSV / XML, or pull out any subtree as JSON
• 📋 Right-click to copy a key, value, or jq-style path
• 🔗 Union multiple files into one searchable tree
• 📄 NDJSON / JSON Lines auto-detected · 20-language UI · 100% offline, no telemetry
It started as a macOS weekend hack; since then it's grown to Windows, streaming CSV/XML/JSON export, clipboard extract, and a round of performance tuning — all in the open. It's 100% free and open source (MIT) — including commercial use and every feature, no limits.
⭐ Source code: https://github.com/bandusix/huge...
🌐 Site & downloads: https://bandusix.github.io/huge-...
I'd genuinely love feedback — especially files that break it. What's the biggest JSON you've ever had to open? 🙏
Opened a 2.5 GB log dump I'd been avoiding for weeks and the search returned results almost instantly. Genuinely useful for anyone stuck squinting at JSON in a text editor.
Finally a free option that actually opens my 2GB log dumps without choking. The regex search across the whole tree is exactly what I needed for debugging those nested payloads.
Opened a 2.5 GB log dump I'd been dreading and the tree viewer rendered in a few seconds, search through nested keys actually felt instant. Really handy for anyone stuck paying for Dadroit.
About BigJSON on Product Hunt
“Free, open-source large JSON file viewer Dadroit alternative”
BigJSON was submitted on Product Hunt and earned 0 upvotes and 4 comments, placing #152 on the daily leaderboard. Open and search multi-gigabyte (2–3 GB) JSON files on macOS and Windows in seconds. A free, open-source alternative to Dadroit: tree viewer, key & value RegEx search, copy & extract any value or subtree, JSON to CSV/XML export, and multi-file union. No cost, no limits, commercial use free.
BigJSON was featured in Open Source (68.6k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 38.5k products, making this a competitive space to launch in.
Who hunted BigJSON?
BigJSON was hunted by Nicholas T. Rigby. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how BigJSON stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Nicholas T. Rigby