Monitor, Debug & Audit Your Valkey
Persistent observability for Valkey — debug incidents yourself or with your agent, hours after they happen, or be proactively notified via webhooks before they start. Redis-compatible.
Or self-host:
claude mcp add betterdb -- \ npx @betterdb/mcp betterdb-mcp \ --autostart --persist
Adds BetterDB as an MCP server to Claude Code. Starts monitoring automatically.
Then ask Claude about your database health, slow queries, or memory usage.
See what's actually happening inside your Valkey instance
Historical data that survives a log rotation. Client-level attribution. Automatic anomaly detection.
500 slow queries, 114 unique patterns, 19 command types — across any historical time range. The evidence that used to disappear after a log rotation.
Built for humans and agents alike
Investigate incidents yourself — or point your agent at BetterDB and walk away.
Your agent investigates
Connect BetterDB's MCP server to Claude Code, Cursor, or any MCP-compatible client. Ask questions in plain language. Get back structured diagnostics — slowlog history, anomaly summaries, latency trends, ACL audit — without opening a browser.
{
"mcpServers": {
"betterdb": {
"command": "npx",
"args": ["-y", "@betterdb/mcp"]
}
}
}You investigate
Full dashboard, slowlog pattern analysis, anomaly detection, client attribution, and vector search — everything you need to find what went wrong and why, with data that persists beyond the log rotation.
Everything you need to understand your Valkey instance
Deep insights into your Valkey deployment with minimal overhead.
COMMANDLOG Support
Valkey 8.1+ exclusive. See every command executed, not just slow ones.
Anomaly Detection
Automatic detection of unusual patterns across memory, CPU, and connections.
Historical Analytics
Query what happened at 3am, not just what's happening now.
Cluster Visualization
Interactive topology graphs, slot heatmaps, and migration tracking.
ACL Audit Trail
Track who accessed what for compliance and debugging.
Slowlog Patterns
See that GET user:* is 80% of your slow queries.
Key Analytics
Analyze key patterns by namespace and key type.
Client Analytics
See which clients consume resources. Detect unusual buffer sizes and connection spikes.
Prometheus & Webhooks
101 Prometheus metrics plus Slack, email, and webhook notifications.
AI Assistant
Ask questions about your Valkey instance in plain English.
Vector Search
Inspect vector indexes, browse embeddings, and find semantically similar entries with similarity scores.
MCP Server
Access BetterDB's full functionality from any MCP-compatible client — Claude Code, CLI agents, or IDEs.
View on registry →Hot Key Tracking
Top-50 keys by access frequency with rank movement over time. Spot what's climbing before it becomes a bottleneck.
Latency Monitoring
Per-event latency history across P50/P95/P99. Know when your instance started slowing down, not just that it is.
CPU & I/O Threads
Per-thread I/O metrics and CPU utilization charts. Valkey-specific visibility no Redis tool can provide.
Semantic caching — the only one built for Valkey
@betterdb/semantic-cache drops into any LLM app and cuts API costs by serving semantically similar responses from Valkey. No framework lock-in. And because it runs on the same Valkey instance you're already monitoring, BetterDB surfaces hit rate, similarity scores, and cost savings automatically.
Valkey-native
Handles valkey-search API differences explicitly. Works on ElastiCache, Memorystore, or self-hosted. Not a Redis port.
Standalone
Any LLM client — OpenAI, Anthropic, local model. No LangChain, no LiteLLM required.
Full observability
Every check() and store() emits OTel spans and Prometheus metrics. Hit rate, similarity scores, latency — zero extra instrumentation.
Every other library makes you pick two.
| Library | Valkey-native | Standalone | Built-in OTel + Prometheus |
|---|---|---|---|
| @betterdb/semantic-cache | ✅ | ✅ | ✅ |
| RedisVL SemanticCache | ❌ Redis only | ✅ | ❌ |
| LangChain RedisSemanticCache | ❌ Redis only | ❌ Requires LangChain | ❌ |
| LiteLLM redis-semantic | ❌ Redis only | ❌ Requires LiteLLM | ❌ Partial |
| Upstash semantic-cache | ❌ Upstash only | ✅ | ❌ |
| Redis LangCache | ❌ Redis Cloud only | ❌ Managed only | ✅ Dashboard only |
import Valkey from 'iovalkey';
import { SemanticCache } from '@betterdb/semantic-cache';
const cache = new SemanticCache({
client: new Valkey({ host: 'localhost', port: 6399 }),
embedFn: yourEmbedFn, // OpenAI, Voyage, Cohere, local — anything
});
await cache.initialize();
await cache.store('What is the capital of France?', 'Paris');
const result = await cache.check('Capital city of France?');
// result.hit === true — LLM call skippedOur goal: zero Valkey hacks
If you've ever written a custom script, stitched together three tools, or just accepted that something wasn't observable - we want to hear about it. Tell us what's missing. We'll build it, and the next person won't have to figure it out themselves.
Book 15 min with KristiyanPrefer email? kristiyan@betterdb.com
Launch Special — Use license key beta for full Pro features
Ready to get started?
Start monitoring in minutes — no infrastructure to maintain. Team collaboration, agent-based monitoring for private databases, and more. Or self-host — open source core, zero lock-in.