SuperAPI – API Caching with Automatic Invalidation (No Code Changes)

Hacker News

Hey HN We built SuperAPI ( https://trysuperapi.com ) to solve a pain many devs know too well: API performance and caching are hard, especially when dealing with dynamic data and invalidation logic. SuperAPI is a plug-and-play caching layer that: - Sits in front of your load-balancer - Caches responses out of the box - Automatically invalidates relevant cache entries when your database changes - Requires zero code changes This interactive playground shows exactly how it works: - Run real queries against a sample API - Watch cache hits and misses live - Update the DB and see the cache invalidate — automatically Would love your feedback on anything that isn't clear on how SuperAPI works. Thanks — Ayush, Hrithik & Adithya from SuperAPI

Visit product View on Hacker NewsApr 23, 2025

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

83%83% 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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% 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

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

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

25%25% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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