Goms is a ready-to-deploy schema driven adaptable platform

Hacker News

https://goms-demo.herokuapp.com This is a very early stage demo for Goms. 1. Independent User registration / User sign-in You can create a public site or a private site, or mixed. Was using auth0 earlier but felt it as an extra step during setup. Authentication/Authorization is a first class component. 2. Native support for user defined entities Create extensively related entities, eg. (Clothing)"Style" has a "Style File", some "Order" and "Costing", and "Order" has "Vendor" associated to it. Entities you see in this demo are defined here [1], [2] 3. Oauth Connections and Tokens ( Live Sync Google Sheet [3] ) We are handling "data exchange" with the external world (think google sheets, slack messenger, other APIs) as a first class citizen. To demo this, four of the entities defined (using our JSON above) are synced to this Google sheet [3] - Blog - Style - Order - Vendor Whenever one of these is created, goms will call one/some REST API. - Oauth connection details configured using JSON files - Access tokens and refresh tokens:, complete oauth2 flow - Tokens/passwords stored securely to avoid accidental leak 4. Behind the scenes - Everything is backed by a relational database - Built in golang with goals to compile for IOT devices as well - The view/dashboard is completely detached from the backend [1] https://github.com/artpar/goms/blob/master/gomsweb/static/samples/blog.json [2] https://github.com/artpar/goms/blob/master/gomsweb/static/samples/style.json [3] https://docs.google.com/spreadsheets/d/1Ru-bDk3AjQotQj72k8SyxoOs84eXA1Y6sSPumBb3WSA/edit?usp=sharing [4] https://developers.google.com/sheets/api/reference/rest/v4/spreadsheets.values/append Github: https://github.com/artpar/goms You can deploy using readily available docker -p 8080:8080 run goms/goms , or "Deploy to Heroku" button. Would love feedback on all parts of Goms. Plus welcome hackers who can help in identifying holes. PS: this is a demo instance. please use dummy details to sign up. nothing is tracked though.

Visit product View on Hacker NewsJun 29, 2017

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

78%78% 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: slack, google, user · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% 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: google · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% 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 · 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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