Open-source reverse ETL – for devs and analysts to show business impact

Hacker News

Founder here. I want to show you Multiwoven - open-source Reverse ETL. I’ve spent close to two decades in jobs where data devs and business teams have been at loggerheads. Business balks at the long lead time for data requests or custom integrations. And data devs (or analysts/ops) hate the tediousness of these tasks. With the amount of data being captured and modeled only growing - Multiwoven’s been built for anyone to use the rapidly growing amounts of data in warehouses like Snowflake, BigQuery, Redshift, Postgres and Databricks - for easy preparation and sync to marketing, sales and other business tools. It’s been built using Ruby on Rails, ReactJS, TypeScript and Temporal. Data devs are under a lot of pressure to show business impact from data, especially in this economy. Developers have to tediously build (and maintain!) custom integrations & data pipelines themselves or have to consider purchasing expensive CDPs built for marketers, or third-party rETL SaaS tools. I also believe that people shouldn’t have to pay to move their own data to their own tools, and that it’s risky to hand over access of sensitive customer data to third-party SaaS tools. We’re open-source (data movement infra is free) and self-hosted (so data is in your control and never leaves the premises). Would love to get your feedback, as an early stage project.

Visit product View on Hacker NewsFeb 20, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, tasks, using · 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

66%66% 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 · Strong signals: para · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

22%22% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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