Nitrite Database – An embedded NoSQL database for apps

Hacker News

Nitrite is a server-less, embedded NoSQL database. It is opensource and is designed to be lightweight, fast, and easy to use. Currently, it is available in Java, Kotlin, and Flutter. It has features like: - Embedded, server-less - Simple API - Document-oriented - Schemaless document collection and object repository - Extensible storage engines - Indexing and full-text search - Simple query API - In-memory and file-based store - Transaction support - Schema migration support - Encryption support Nitrite is ideal for uses cases like: - Mobile and desktop applications - IoT devices and sensors - Web applications and APIs - Prototyping and testing - Data caching and synchronization - Data analysis and reporting where a lightweight, embedded, and server-less NoSQL database is required.

Visit product View on Hacker NewsJan 15, 2024

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

74%74% 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.

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

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

52%52% 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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% 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

19%19% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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