Atlas – Open-source Mixpanel/Amplitude alternative

Hacker News

Hey everyone! I'm excited to share my newest side project, Atlas. Atlas is an open-source product analytics tool that sits on top of the data warehouse. You can do things like funnels, flows, and retention analysis that typically you need to pipe data to Mixpanel or Amplitude for. Under the hood, it uses dbt to run queries and is built using TypeScript, React, and NextJS. Check out the live demo at https://atlas-demo.onrender.com/ and let me know if you have questions or thoughts. Happy Atlasing!

Visit product View on Hacker NewsOct 13, 2022

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

91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

48%48% 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

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

30%30% 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

12%12% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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