AGX – Open-Source Data Exploration for ClickHouse (The New Standard?)

Hacker News

Hey HN, We are excited to announce that we’ve open-sourced AGX, a fast and lightweight data explorer for ClickHouse. It is designed for developers and analysts who want to leverage SQL-native querying in an IDE-like environment. Here’s what makes AGX stand out: - Built on ClickHouse (accessible via embedded chdb or remote instance). - IDE-like user interface: features tabs, a Monaco editor, and a fast keyboard workflow. - Zero setup required: no infrastructure or complex dashboards to manage. - Ideal for exploring live blockchain data, while also flexible enough for general ClickHouse usage Think of it as a snappier, developer-oriented alternative to Tabix or Datagrip. You can try out a live instance at https://agx.app !

Visit product View on Hacker NewsMar 19, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos

95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

90%90% 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 · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, 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.

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