mirror of
https://github.com/qdrant/landing_page.git
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Abdon Pijpelink
45f19f30ee
* Add new Scaling landing page under Operations Introduces a Scaling section with vertical vs. horizontal scaling guidance and failover best practices, linking out to detail pages. * Add new Vertical Scaling page Dedicated how-to guidance for resizing existing nodes: when to scale vertically, RAM sizing formulas, and Cloud/self-hosted resize steps. * Add new Horizontal Scaling and Resilience page Covers Raft consensus, the replication model, consistency guarantees, Multi-AZ, and the resilience terminology used elsewhere in the docs. * Move Distributed Deployment under Scaling and update all incoming links Moves distributed_deployment.md into the new scaling/ section, trims its Raft/Replication/Consistency intros into cross-links to the new Horizontal Scaling and Resilience page, adds Multi-AZ and single-replica cross-link callouts in the Cloud docs, rewrites all internal references across ~30 files to the new canonical path instead of relying on aliases, and applies Title Case to Distributed Deployment's headers. * Split Resilience out of Horizontal Scaling and Resilience Adds a dedicated Resilience page covering fault tolerance, Multi-AZ, resilience terminology, and failover best practices (moved from the Scaling landing page). Horizontal Scaling is retitled and scoped to the underlying mechanics: Raft consensus, replication, and consistency. * Reorganize Horizontal Scaling's structure Moves "How Many Qdrant Nodes Should I Run?" from Distributed Deployment into Horizontal Scaling, adds a conceptual Sharding section, and reorders Sharding/Replication/Raft Consensus/Consistency. Moves the remaining conceptual content out of Distributed Deployment: Temporary Node Failure to Resilience, Error Handling folded into Replication, sharding heuristics folded into Sharding, and the Consensus Checkpointing explanation folded into Raft Consensus. * Rename Scaling section to Scaling & Resilience Renames the section and restructures the landing page: the vertical- vs-horizontal decision is now purely about scaling, with a dedicated Resilience section covering fault tolerance through sharding and multi-node deployments. * Polish Vertical Scaling and Resilience page content Reframes Vertical Scaling's "What Not to Do" as positive "Best Practices". Reworks Resilience's structure: moves the uptime/data- integrity terminology into the intro as three distinct aspects of resilience, and renames "How Resilience Works" to "Setting Up a Resilient Qdrant Cluster". * Add diagrams illustrating sharding and replication Adds cluster diagrams to the Sharding and Replication sections on Horizontal Scaling to make the shard/replica layout easier to follow. * Add new Node Failure Recovery page Extracts the node failure recovery scenarios out of Distributed Deployment into their own page, with each bolded sub-header converted to a proper heading, and links updated across Resilience and the Scaling landing page. * Add new Consistency Guarantees page Extracts write consistency factor, read consistency, and write ordering out of Distributed Deployment into their own page, positioned after Distributed Deployment. * Add new "Deploy Behind a Load Balancer" section Explains why a load balancer is needed in front of a multi-node Qdrant cluster: avoiding a single point of failure at the entry point and making sure replicas on every node actually serve reads. * Add new "Rebalancing" section Documents how Qdrant Cloud automatically rebalances shards across nodes, as its own subsection under Sharding. * Rewrite Multi-AZ vs. Replication Factor as Multi-AZ Deployments Defines an availability zone on first use, explains why multi-AZ deployments guard against a zone going down, clarifies that Qdrant Cloud is zone-aware once enabled, and that self-hosted deployments need to place and move replicas across zones manually. * Restructure node-count guidance into One/Two/Three-or-more Node subsections Splits "How Many Qdrant Nodes Should I Run?" into three subsections and drops the "balanced" framing for two nodes: it states plainly that two nodes give more capacity without true high availability. * Add new "Which Configuration Is Right for You?" section Summarizes the one/two/three-or-more node tradeoffs in one place right after the detailed breakdown. * Add explicit _redirects entry for legacy distributed_deployment URL Closes the redirect chain: the existing /guides/ and /operations/ legacy rules both terminate at /documentation/distributed_deployment/, which previously had no explicit _redirects entry and only resolved via the Hugo alias meta-refresh page. * Fix all incoming links to Distributed Deployment and pages under Scaling Repoints two same-page anchors in distributed_deployment.md that broke when Write Ordering moved to Consistency Guarantees, and one link in cloud/create-cluster.md that broke when a Resilience heading was reworded. * Update time-based sharding diagram and restructure section * Fix a couple of broken links * Move 'Consensus Checkpointing' to 'Node Failure Recovery' page
145 lines
9.0 KiB
Markdown
145 lines
9.0 KiB
Markdown
---
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title: Documentation
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short_description: "Build with Qdrant: install, run, and scale a vector search engine across self-hosted, Cloud, Hybrid Cloud, and Private Cloud deployments."
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description: "Official Qdrant documentation for vector search and retrieval — quickstarts, deployment guides, integrations, and references for self-hosted and Qdrant Cloud."
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weight: 2
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hideTOC: true
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breadcrumb: false
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content:
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- partial: "documentation/banners/banner-a"
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title: Qdrant Documentation
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description: Qdrant is an AI-native vector search and a semantic search engine. You can use it to extract meaningful information from unstructured data.
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linkDescription: <a href="https://github.com/qdrant/qdrant_demo/" target="_blank">Clone this repo now</a> and build a search engine in five minutes.
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cloudButton:
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text: Cloud Quickstart
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url: /documentation/cloud-quickstart/
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localButton:
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text: Local Quickstart
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url: /documentation/quickstart/
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contained: true
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- partial: documentation/banners/banner-d
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developingTitle: Introducing Qdrant Edge
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developingDescription: Qdrant Edge is a lightweight, embedded vector search engine for in-process retrieval — no background services, minimal memory footprint, and no network required. Built for robots, kiosks, mobile devices, and any environment requiring offline-capable AI search.
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developingBlock:
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title: Run vector search anywhere, even offline
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button:
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text: Get Started
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url: /documentation/edge/edge-quickstart/
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image:
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src: /img/rocket.svg
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alt: Rocket
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- partial: documentation/sections/cards-section
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title: Qdrant User Manual
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description: Learn how to manage your data, run powerful searches, and leverage inference to build AI-native applications.
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cardsPartial: documentation/cards/docs-cards
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cards:
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- id: 1
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icon:
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src: /icons/outline/vectors-blue.svg
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alt: Vectors
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title: Manage Data
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description: Create collections, manage vectors, payloads, and storage. Learn about indexing, quantization, and multitenancy.
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link:
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url: /documentation/manage-data/
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text: Read More
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- id: 2
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icon:
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src: /icons/outline/search-blue.svg
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alt: Search
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title: Search
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description: Learn about similarity search, filtering, hybrid queries, and advanced retrieval techniques.
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link:
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url: /documentation/search/
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text: Read More
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- id: 3
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icon:
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src: /icons/outline/integration-blue.svg
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alt: Inference
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title: Inference
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description: Configure dense, sparse, and multi-vector embeddings. Use cloud-hosted embedding models directly with Qdrant.
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link:
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url: /documentation/inference/
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text: Read More
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- partial: documentation/sections/cards-section
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title: Support
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description: Get help from the Qdrant community or contact our support team.
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cardsPartial: documentation/cards/docs-cards
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cardsPerRow: 2
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cards:
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- id: 1
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icon:
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src: /icons/outline/discord-purple.svg
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alt: Discord icon
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title: Community Support
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description: Join 6,000+ active members to learn, collaborate, and participate in Qdrant's latest activities.
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link:
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text: Join our Discord
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url: https://qdrant.to/discord
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- id: 2
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icon:
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src: /icons/outline/support-blue.svg
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alt: Support icon
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title: Qdrant Cloud Support
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description: Paying customers have access to our Support team. Links to the support portal are available in the Qdrant Cloud Console.
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link:
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text: Join Qdrant
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url: https://qdrant.to/cloud
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partition: develop
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---
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# Qdrant Documentation
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Qdrant is an AI-native vector search engine for storing, indexing, and searching high-dimensional vectors — powering semantic search, RAG pipelines, recommendation systems, and AI-native applications.
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## Getting Started
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- [Local Quickstart](/documentation/quickstart/index.md) — Run Qdrant locally with Docker, connect a client SDK, and create your first collection.
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- [Cloud Quickstart](/documentation/cloud-quickstart/index.md) — Create a free Qdrant Cloud cluster on AWS, GCP, or Azure and query it in minutes.
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- [Overview](/documentation/overview/index.md) — How vector search works, the client-server architecture, and core data structures (points, vectors, payloads, collections).
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- [API & SDKs](/documentation/interfaces/index.md) — Connect via REST or gRPC with official client libraries for Python, JavaScript/TypeScript, Rust, Go, Java, and .NET.
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## Develop
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- [Manage Data](/documentation/manage-data/index.md) — Create collections, insert and update points and payloads, configure vector indexes, quantization, and multitenancy.
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- [Search](/documentation/search/index.md) — Similarity search, filtering, hybrid and multimodal queries, multi-stage pipelines, and relevance tuning.
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- [Inference](/documentation/inference/index.md) — Configure dense, sparse, and multi-vector embeddings; use cloud-hosted embedding models directly within Qdrant.
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- [Qdrant Edge](/documentation/edge/index.md) — Lightweight embedded vector search for in-process, offline-capable retrieval on robots, kiosks, and mobile devices.
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## Deploy
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- [Deploy Overview](/documentation/deploy-intro/index.md) — Compare all Qdrant deployment options: Managed Cloud, Hybrid Cloud, Private Cloud, and self-hosted.
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- [Installation](/documentation/installation/index.md) — Install Qdrant via Docker, Kubernetes, or binary on Linux, macOS, or Windows.
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- [Managed Cloud](/documentation/cloud/index.md) — Qdrant as a managed service on AWS, GCP, or Azure with automatic scaling, backups, and zero-downtime upgrades.
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- [Hybrid Cloud](/documentation/hybrid-cloud/index.md) — Deploy into your own Kubernetes cluster while managing through Qdrant Cloud.
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- [Private Cloud](/documentation/private-cloud/index.md) — Fully air-gapped deployment in your own Kubernetes cluster with no Qdrant Cloud connectivity required.
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- [Distributed Deployment](/documentation/scaling/distributed_deployment/index.md) — Multi-node clusters with horizontal sharding and replication for scale and fault tolerance.
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- [Security](/documentation/security/index.md) — API keys, JWT-based collection-scoped access control, TLS encryption, and network binding.
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- [Configuration](/documentation/ops-configuration/index.md) — Customize Qdrant via config files and environment variables; runtime administration tools; GPU-accelerated vector indexing.
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- [Monitoring & Telemetry](/documentation/ops-monitoring/index.md) — Monitor Qdrant with Prometheus and Grafana via built-in OpenMetrics endpoints.
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- [Optimization](/documentation/ops-optimization/index.md) — Tune for high-speed search, high precision, or low memory usage; understand how the background optimizer works.
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- [Production Checklist](/documentation/production-checklist/index.md) — Pre-launch review of sharding, replication, quantization, load balancing, and observability.
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- [Capacity Planning](/documentation/capacity-planning/index.md) — Estimate RAM and disk for vectors, payloads, indexes, and replication factors.
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- [Snapshots](/documentation/snapshots/index.md) — Back up and restore collections with snapshots for disaster recovery and cross-cluster replication.
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- [Troubleshooting](/documentation/common-errors/index.md) — Diagnose common runtime errors: open-file limits, filesystem incompatibilities, corrupted collection metadata.
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## Ecosystem
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- [Frameworks](/documentation/frameworks/index.md) — Integrations with 40+ AI agent and RAG frameworks: LangChain, LlamaIndex, Haystack, CrewAI, AutoGen, Spring AI, and more.
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- [Embedding Providers](/documentation/embeddings/index.md) — Connect to 30+ providers: OpenAI, Cohere, Jina, Mistral, AWS Bedrock, Voyage AI, Ollama, and more.
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- [Platforms](/documentation/platforms/index.md) — No-code and low-code integrations with n8n, Make, MuleSoft, Pipedream, and more.
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## Tutorials & Examples
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- [Tutorials](/documentation/tutorials-lp-overview/index.md) — Hub for all tutorials covering basics, search engineering, retrieval quality, operations, migrations, and ecosystem integrations.
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- [Examples](/documentation/examples/index.md) — End-to-end code samples for RAG pipelines, hybrid search, multitenancy, recommendations, and multimodal search.
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## Learn
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- [Articles](/articles/index.md) — Long-form articles on vector search, RAG, quantization, hybrid retrieval, and Qdrant internals from the engineering team.
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- [Qdrant Academy](/course/index.md) — Free, self-paced courses on vector search, hybrid retrieval, multivectors, and production-grade AI search applications.
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- [Tutorials](/documentation/tutorials-lp-overview/index.md) — Hub for all tutorials covering basics, search engineering, retrieval quality, operations, migrations, and ecosystem integrations.
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## API Reference
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- [Qdrant API Reference](https://api.qdrant.tech/api-reference) — Full REST API reference for all Qdrant operations: collections, points, search, indexing, cluster management, and more.
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