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BetterDB – Valkey/Redis monitoring that persists what servers forget

BetterDB – Valkey/Redis monitoring that persists what servers forget

by kaliades·Feb 12, 2026·4 points·0 comments
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AI Analysis

●●●BangerSolve My ProblemBig BrainDark Horse

Persists Redis/Valkey's ephemeral observability data with rigorous interleaved benchmarking proving sub-1% overhead.

Strengths
  • •Solves a real, acute pain: Redis/Valkey data vanishes on restart. Historical context matters for debugging.
  • •Interleaved benchmarking methodology is genuinely rigorous—eliminates thermal throttling and confounding variables that fake overhead claims.
  • •Deep feature set (anomaly detection, cluster topology, AI query assistant) built by Redis Insight's former lead—deep domain expertise.
Weaknesses
  • •Market is small: only relevant to Valkey/Redis ops teams. Not a horizontal tool.
  • •Pricing and ease of deployment unclear from landing page alone—SaaS adoption depends on smooth onboarding.
Target Audience

DevOps engineers, SREs, and platform teams running Valkey or Redis in production.

Similar To

Redis Cloud observability dashboards · Datadog/New Relic Redis monitoring modules · RedisInsight (official Redis GUI)

Post Description

Hey HN, I'm Kristiyan. I previously led Redis Insight (the official Redis GUI). When I started working with Valkey, I found the observability tooling lacking — so I started building BetterDB.

The core problem: Valkey and Redis expose useful operational data (slowlog, latency stats, client lists, memory breakdowns), but it's all ephemeral. Restart your server and it's gone. Existing tools show real-time charts but can't tell you what happened at 3am when your p99 spiked.

BetterDB persists this ephemeral data and turns it into actionable insights:

- Historical analytics for queries (slowlog and commandlog patterns aggregated by type), clients (commands, connections, buffers), and ACL activity - Anomaly detection and 99 Prometheus metrics - Cluster visualization with topology graphs and slot heatmaps - Automated latency and memory diagnostics - AI assistant for querying your instance in plain English (via local Ollama) - Sub-1% performance overhead

On that last point — I wrote up our interleaved A/B benchmarking methodology in detail: https://www.betterdb.com/blog/interleaved-testing. Most tools claim "minimal overhead" without showing their work. We open-sourced the benchmark suite so you can run it on your own hardware and verify.

You can try it right now:

npx @betterdb/monitor

Or via Docker:

docker run -d -p 3001:3001 betterdb/monitor

BetterDB follows an open-core model under the OCV Open Charter (which prevents future licensing changes). The community edition is free with real monitoring value. Pro and Enterprise tiers add historical persistence, alerting, and compliance features, but are free for now and will be at least until end of month.

We're building this in public — the benchmark suite, the technical blog posts, and the roadmap are all out in the open. Would love feedback from production users of Valkey or Redis on what observability gaps you're still hitting.

GitHub: https://github.com/BetterDB-inc/monitor Blog: https://www.betterdb.com/blog

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