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Searchkit V3: GraphQL and React Toolkit for Elasticsearch

Hacker News

Searchkit V3: GraphQL and React Toolkit for Elasticsearch

Hi guys! Yesterday I released an rc for v3 which was a near rewrite to make Searchkit easier to use. Been 2 years since its last release. The previous version had its own UI framework and worked solely on the browser. In this version, i've split it out into three tiers and heavily relied on Apollo GraphQL and @elastic/eui framework. Github: www.github.com/searchkit/searchkit Demo: http://demo.searchkit.co/ Docs: https://searchkit.co/docs Why GraphQL? https://blog.searchkit.co/searchkit-why-graphql-aa886603b698 Love to hear some feedback on this as im still refining the GraphQL schema and the docs are not great. Joe

Visit product View on Hacker NewsNov 15, 2020

Actual performance

2points

3comments

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

21%21% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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