Talk to Your S3 Data

Hacker News

A lot of people that sign up for Definite ( https://www.definite.app/ ) have much of their data sitting in S3 / GCP. Most BI tools need you to pipe that data into a SQL database / data warehouse, but that can be expensive and a pain to set up. We've seen this enough times that we added some features to directly query S3 without moving the data. Under the hood, our product[0] uses DuckDB as a data warehouse. DuckDB has some amazing features that made it pretty easy on our end. Here's how it works ( https://www.youtube.com/watch?v=yrrCQnfKEig ): 1. Add an S3 / GCP key and secret 2. Write a little SQL to access the data you care about (e.g. CSVs, parquet, JSON, JSONL, etc.) 3. Build a model on top of that data (we automatically create a basic model which you can tweak) 4. Share that model with non-technical business users (if they can use a pivot table, they'll be able to use Definite) 5. Ask our AI ("Fi") questions about the data. Fi can build reports and dashboards on top of S3. 0 - https://www.definite.app/

Visit product View on Hacker NewsApr 15, 2024

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

84%84% 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 · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

70%70% 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: users · Missing: mobile apps, ios, personal

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% 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

16%16% 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.

Incorrect prediction on native model

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