Production engineering reference for running Apache JanusGraph at scale.
Hardened backend configuration, deterministic index synchronization, resilient Python pipelines, and the observability to keep them healthy.
🌐 Read it at storagebackend.org →
storagebackend.org is a deep, hands-on reference for the hardest part of operating Apache JanusGraph in production: the seam where a distributed graph engine meets its pluggable storage and index backends. JanusGraph decouples storage, indexing, and compute into three independently scaled tiers — architectural flexibility that turns every write into a distributed-consistency problem you have to engineer explicitly.
Most JanusGraph material stops at "it works on my laptop." This site starts where that ends: what actually happens under sustained ingestion, where drift originates, and exactly which command confirms a diagnosis at 3 a.m. Every page is written for on-call distributed-systems engineers — a concrete problem statement, an architecture diagram, an annotated configuration block, runnable gremlin-python / CQL / Java, and explicit failure-mode triage with verification and rollback steps.
55 in-depth guides. ~170,000 words. Zero fluff.
- 🗄️ Storage Backend Architecture & Configuration — Production configuration for Cassandra and ScyllaDB backends: consistency levels, connection pooling, replication topology, bulk data loading, backend selection and capacity sizing, and ScyllaDB migration playbooks.
- 🔄 Index Synchronization & Consistency Tuning — Keeping Elasticsearch and OpenSearch aligned with the graph: mixed-index routing, sync patterns, drift recovery, reindexing, and the eventual-versus-strong-consistency tradeoffs that decide whether a query can read its own write.
- 🛡️ Schema Validation & Modeling — Enforcing graph integrity: vertex and edge validation, property indexing rules, schema evolution with CI gating, online schema migrations, and alert routing for violations.
- 📈 Monitoring & Observability — Making storage and index behavior measurable: Prometheus and JMX metric catalogs, Grafana dashboards, and alerting thresholds that page a human before drift becomes an incident.
- Actionable, not explanatory. Every section is a command, a config value with its rationale, or a runnable code block — the shape an operator needs, not a conceptual tour.
- Original diagrams. Every architecture, data-flow, and state diagram is a hand-authored, theme-aware, accessible inline SVG built specifically for the concept it explains.
- Densely cross-linked. Named concepts link to their own dedicated guide the first time they appear, so you can follow a failure from symptom to root cause across the whole reference.
- Fast and resilient. A static site with a strong mobile performance budget, full WCAG 2 AA accessibility, structured data on every page, and offline support as an installable PWA.
- Eleventy — static site generation
- markdown-it + Prism + KaTeX — content, syntax highlighting, and math rendering
- Cloudflare Workers — edge delivery
- Hand-authored inline SVG, a service worker for offline use, and a strict quality-gate suite (accessibility, structured data, performance, link integrity, and more) that every page must pass before it ships
npm install # install dependencies
npm run serve # local dev server with live reload at http://localhost:8080
npm run build # production build to _site/
npm run deploy # build and deploy to CloudflareStart with the section that matches your current bottleneck, or follow the links between guides to build a complete operational picture — from a single hardened janusgraph.properties baseline all the way to a full monitoring and alerting stack.