qdrant-deployment-options
Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which deployment option', 'self-hosted vs cloud', or 'need lowest latency deployment'. Also use when choosing between deployment types for a new proje
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SKILL.md
Which Qdrant Deployment Do I Need?
Start with what you need: managed ops or full control? Network latency acceptable or not? Production or prototyping? The answer narrows to one of four options.
Getting Started or Prototyping
Use when: building a prototype, running tests, CI/CD pipelines, or learning Qdrant.
- Use local mode (Python only): zero-dependency, in-memory or disk-persisted, no server needed Local mode
- Local mode data format is NOT compatible with server. Do not use for production or benchmarking.
- For a real server locally, use Docker Quick start
Going to Production (Self-Hosted)
Use when: you need full control over infrastructure, data residency, or custom configuration.
- Docker is the default deployment. Full Qdrant Open Source feature set, minimal setup. Quick start
- You own operations: upgrades, backups, scaling, monitoring
- Must set up distributed mode manually for multi-node clusters Distributed deployment
- Consider Hybrid Cloud if you want Qdrant Cloud management on your infrastructure Hybrid Cloud
Going to Production (Zero-Ops)
Use when: you want managed infrastructure with zero-downtime updates, automatic backups, and resharding without operating clusters yourself.
- Qdrant Cloud handles upgrades, scaling, backups, and monitoring Qdrant Cloud
- Supports multi-version upgrades automatically
- Provides features not available in self-hosted:
/sys_metrics, managed resharding, pre-configured alerts
Need Lowest Possible Latency
Use when: network round-trip to a server is unacceptable. Edge devices, in-process search, or latency-critical applications.
- Qdrant EDGE: in-process bindings to Qdrant shard-level functions, no network overhead Qdrant EDGE
- Same data format as server. Can sync with server via shard snapshots.
- Single-node feature set only. No distributed mode.
What NOT to Do
- Use local mode for production or benchmarking (not optimized, incompatible data format)
- Self-host without monitoring and backup strategy (you will lose data or miss outages)
- Choose EDGE when you need distributed search (single-node only)
- Pick Hybrid Cloud unless you have data residency requirements (unnecessary Kubernetes complexity when Qdrant Cloud works)
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1- SKILL.md
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