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Products that do what See – searchable JSON compression (offline 10-min demo) does

Hi HN, I’m building SEE (Semantic Entropy Encoding): a searchable compression format for JSON/NDJSON. Goal: reduce the “data tax” (storage/egress) and “CPU tax” (decompress/parse) by keeping JSON searchable while compressed, with page-level random access. I just published a proof-first evaluation release: Offline DEMO ZIP (~10 min): prints compression ratios + skip rates + lookup latency (p50/p95/p99) DD pack: audit/repro evidence (decode mismatch=0, extended mismatch=0, audit PASS) Latest release:…

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    We've all been there: you have some JSON data you need to make sense of, so you Google "json formatter" and end up at a site ridden with ads. I used to look at at lot of JSON (mostly log data) for $oldjob, so I set out to build something better. I know there are a lot of tools in this space, but I've put a lot of love into JSON Dive: things like Vim keyboard shortcuts to navigate, dark mode, timestamp/image previews, and multi-file-format-support (XML-in-JSON was a format I dealt with in the context of LLMs/tool calls). I've also made an effort to ensure it can handle large files,…

    Sep 2025 · jsondive.app

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    2013 · jsonblob.com

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    2015 · json-diff.com

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    2020 · jsonformatter.live

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    I’ve been working on a compression algorithm for fast random access to individual strings in large collections. The problem came up when working with large in-memory database columns (emails, URLs, product titles, etc.), where low-latency point queries are essential. With short strings, LZ77-based compressors don’t perform well. Block compression helps, but block size forces a trade-off between ratio and access speed. Some existing options: - BPE: good ratios, but slow and memory-heavy - FSST (discussed here: https://news.ycombinator.com/item?id=41489047): very fast, but…

    2025 · github.com

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    2015 · hperadin.github.io

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    2017 · noisesearch.org

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    Hi HN! Happy to share that jist can now search JSON 17x faster than jq for a provided input (string or a file). The major change is using the bleeding edge simdjson parser as the preferred way of parsing and querying the input. Since simdjson can only work on files up to 4.2GB, jist falls back to its earlier implementation of scanning through input in chunks of 1MB which means it can still query files of virtually infinite size 3x faster than jq ever could while using ~10MB of memory. The next major feature will be summarizing input JSON into a schema - and it will do this by scanning the…

    2025 · github.com

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    2019 · github.com

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