Example Data Service – Lorem Ipsum back ends by @Draftbit (W18)

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Hey there HN! We've created an easy way for you to get started building your next app or no-code project without needing to build the backend first. With over 30 different tables of data, you can use these tables as a great starting point during the design, development, and prototyping phase of building your next app. Check it out at: https://example-data.draftbit.com/ Here are some of the types of apps the data might help you build: - Stock Trading or Crypto Trading - Dating Apps - Restaurant Guides or Local Guides - Addressbooks, Contact Lists, or Team Directories - News or Article focused apps - Todo Lists or Productivity - Ecommerce / Shopping Apps - Music or Podcast Apps - Cars or Enthusiasts Apps - Social Apps - Books or Personal Reading List Apps Many of the tables are linked together with one-to-many or many-to-many relationships and can be queried and interacted with just like a real REST api. So for example, Stocks and Stock Holdings are linked by Users. You can interact with all of this data in a normal way: via API that outputs JSON. You can do any HTTP method on these APIs, like GET or POST, but you can also filter, sort, slice, or paginate the data via URL parameters, just like you would with data from a real REST api. When you start building with real (or at least real-looking) data, you make better design and development choices along the way. You can use this service as a set of example API's for testing your front end development efforts, for building apps in your favorite no-code tool (like @draftbit), or if you just need some example JSON of a certain type. The service is free and does not require any auth or api keys. We'll be adding more data and examples over time! The data used for this service was created or gathered from creative commons and open source sources. Some of it is real data released for machine learning purposes. Thanks! Team Draftbit (W18) https://www.draftbit.com

Visit product View on Hacker NewsJun 8, 2020

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

85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs

68%68% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

35%35% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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