TypeScript ORM with Access Control

Hacker News

ZenStack is built on top of Primsa ORM, extending it with an access control layer that simplifies the development of a web app's backend. By defining authorization policies and validation rules right inside the data schema, database client can automatically enforce these constraints at runtime bringing the following benefits: - Centralized access control for better security and maintainability - Less code to be written The core of ZenStack is a transparent proxy around Prisma client which enforces access policies while keeping the APIs unchanged. It allows building the backend of new projects faster with minimal TS/JS code, and can also be easily adopted into existing projects. Some other benefits it provides: - Automatic CRUD APIs - RESTful, tRPC - Generating client-side data access libraries (aka hooks) - SWR, TanStack Query - A plugin system for 3rd party extension Finally, ZenStack is not opinionated toward any stack or framework, allowing integration with the entire JavaScript and TypeScript ecosystem. GitHub: https://github.com/zenstackhq/zenstack Website: https://zenstack.dev

Visit product View on Hacker NewsJul 25, 2023

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

79%79% 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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% 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 · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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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