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Datagridxl2.js – Fast Excel-like data table library

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Datagridxl2.js – Fast Excel-like data table library

I'm Robbert, the creator of DataGridXL.js. Last month I released version 2 which includes many new features. DataGridXL is a free (and commercial) editable data table library written in ES6. My goal is to develop the most performant & user-friendly spreadsheet-like data table out there: - It has zero dependencies. You don’t need any framework to use DataGridXL. - It is lightweight (~250kb) and easy to use. It does not even require messing with CSS. - It has its own Virtual DOM implementation to prevent DOM errors. - Developer friendly. Supports all modern web browsers Please take a look at the performance demo ( https://www.datagridxl.com/demos/one-million-cells ) to see the difference with other data grids out there. And let us know if you have any suggestions. Please let me know if you have any suggestions or comments!

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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