ReDB – Distributed data mesh for seamless DB replication and access

Hacker News

We just open-sourced reDB: a distributed, policy-driven data mesh that provides real-time access, replication, and migration across databases — including relational, NoSQL, graph, vector, and more. It’s designed for AI systems, developers, and ops teams working in complex, multi-database environments. Highlights: - Unified schema model across database types - Built-in schema version control - Zero-downtime migration and replication - Quantum-safe encryption and data obfuscation - AI agent integration via Model Context Protocol (MCP) GitHub: https://github.com/redbco/redb-open

Visit product View on Hacker NewsJul 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, mcp · 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · 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.

Indie HackersIH features products with proven revenue · Strong signals: including · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% 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

17%17% 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.

Incorrect prediction on native model

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