mirror of
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Merge pull request #2419 from qdrant/szabosteve/agent-friendly-landing
Create an agent-friendlier landing page
This commit is contained in:
István Zoltán Szabó
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partition: develop
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---
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THIS CONTENT IS GOING TO BE IGNORED FOR NOW
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# Qdrant Documentation
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# 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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Qdrant is an AI-native vector search and a semantic search engine. You can use it to extract meaningful information from unstructured data. Want to see how it works? [Clone this repo now](https://github.com/qdrant/qdrant_demo/) and build a search engine in five minutes.
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## Getting Started
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|-:|:-|
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|[Cloud Quickstart](/documentation/cloud-quickstart/)|[Local Quickstart](/documentation/quickstart/)|
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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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## Ready to start developing?
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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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***<p style="text-align: center;">Qdrant is open-source and can be self-hosted. However, the quickest way to get started is with our [free tier](https://qdrant.to/cloud) on Qdrant Cloud. It scales easily and provides an UI where you can interact with data.</p>***
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## Deploy
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[](https://qdrant.to/cloud)
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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/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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## Qdrant's most popular features:
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|[Filterable HNSW](/documentation/search/filtering/) </br> Single-stage payload filtering | [Recommendations & Context Search](/documentation/search/explore/#explore-the-data) </br> Exploratory advanced search| [Pure-Vector Hybrid Search](/documentation/search/hybrid-queries/)</br>Full text and semantic search in one|
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|[Multitenancy](/documentation/manage-data/multitenancy/) </br> Payload-based partitioning|[Custom Sharding](/documentation/distributed_deployment/#sharding) </br> For data isolation and distribution|[Role Based Access Control](/documentation/security/?q=jwt#granular-access-api-keys)</br>Secure JWT-based access |
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|[Quantization](/documentation/manage-data/quantization/) </br> Compress data for drastic speedups|[Multivector Support](/documentation/manage-data/vectors/?q=multivect#multivectors) </br> For ColBERT late interaction |[Built-in IDF](/documentation/manage-data/indexing/?q=inverse+docu#idf-modifier) </br> Advanced similarity calculation|
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## Ecosystem
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## Developer guidebooks:
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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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| [A Complete Guide to Filtering in Vector Search](/articles/vector-search-filtering/) </br> Beginner & advanced examples showing how to improve precision in vector search.| [Building Hybrid Search with Query API](/articles/hybrid-search/) </br> Build a pure vector-based hybrid search system with our new fusion feature.|
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|----------------------------------------------|-------------------------------|
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| [Multitenancy and Sharding: Best Practices](/articles/multitenancy/) </br> Combine two powerful features for complete data isolation and scaling.| [Benefits of Binary Quantization in Vector Search](/articles/binary-quantization/) </br> Compress data points while retaining essential meaning for extreme search performance.|
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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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@@ -110,3 +110,57 @@ hideInSidebar: true
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build:
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render: always
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---
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# Deploy Qdrant
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## 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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- [Distributed Deployment](/documentation/distributed_deployment/index.md) — Multi-node clusters with horizontal sharding and replication for scale and fault tolerance.
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- [Capacity Planning](/documentation/capacity-planning/index.md) — Estimate RAM and disk requirements for vectors, payloads, indexes, and replication factors.
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- [Snapshots](/documentation/snapshots/index.md) — Back up and restore collections for disaster recovery and cross-cluster replication.
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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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- [Upgrades](/documentation/upgrades/index.md) — Upgrade Qdrant clusters across Cloud, Kubernetes, and Docker with zero-downtime planning.
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## Managed Cloud
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- [Managed Cloud](/documentation/cloud/index.md) — Run Qdrant as a managed service on AWS, GCP, or Azure with automatic scaling, backups, and zero-downtime upgrades.
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- [Create a Cluster](/documentation/cloud/create-cluster/index.md) — Launch a free or standard cluster on your preferred cloud provider.
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- [Authentication](/documentation/cloud/authentication/index.md) — Create Database API keys with granular access control and expiration settings.
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- [Cluster Access](/documentation/cloud/cluster-access/index.md) — Connect via REST, gRPC, or the Cluster UI with load-balanced endpoints and IP allowlists.
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- [Configure Clusters](/documentation/cloud/configure-cluster/index.md) — Tune collection defaults, strict mode, replication factor, and optimizer settings.
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- [Scale Clusters](/documentation/cloud/cluster-scaling/index.md) — Scale vertically or horizontally with automatic shard rebalancing.
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- [Monitor Clusters](/documentation/cloud/cluster-monitoring/index.md) — Monitor cluster health with built-in metrics, logs, and email alerts.
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- [Backup Clusters](/documentation/cloud/backups/index.md) — Schedule snapshots and restore clusters for disaster recovery.
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- [Update Clusters](/documentation/cloud/cluster-upgrades/index.md) — Zero-downtime rolling upgrades on multi-node clusters.
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- [Cloud Inference](/documentation/cloud/inference/index.md) — Generate embeddings inside Qdrant Cloud or proxy to OpenAI, Cohere, and Jina.
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## Hybrid Cloud
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- [Hybrid Cloud](/documentation/hybrid-cloud/index.md) — Deploy Qdrant in your own Kubernetes cluster while managing it through Qdrant Cloud.
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- [Setup Hybrid Cloud](/documentation/hybrid-cloud/hybrid-cloud-setup/index.md) — Install and connect the Qdrant Kubernetes Operator to Qdrant Cloud.
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- [Create a Cluster](/documentation/hybrid-cloud/hybrid-cloud-cluster-creation/index.md) — Create a Qdrant cluster in your Hybrid Cloud environment.
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- [Configure, Scale & Upgrade](/documentation/hybrid-cloud/configure-scale-upgrade/index.md) — Tune, resize, and upgrade Hybrid Cloud clusters.
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- [Networking, Logging & Monitoring](/documentation/hybrid-cloud/networking-logging-monitoring/index.md) — Configure networking, ingress, and observability for Hybrid Cloud.
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- [Operator Configuration](/documentation/hybrid-cloud/operator-configuration/index.md) — Advanced configuration of the Qdrant Kubernetes Operator.
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- [Deployment Platforms](/documentation/hybrid-cloud/platform-deployment-options/index.md) — Platform-specific deployment guides for AWS, GCP, Azure, and on-prem Kubernetes.
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## Private Cloud
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- [Private Cloud](/documentation/private-cloud/index.md) — Fully air-gapped Qdrant deployment in your own Kubernetes cluster with no Qdrant Cloud connectivity.
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- [Setup Private Cloud](/documentation/private-cloud/private-cloud-setup/index.md) — Install and configure Qdrant Private Cloud in a Kubernetes cluster.
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- [Cluster Management](/documentation/private-cloud/qdrant-cluster-management/index.md) — Create, manage, and operate clusters in Private Cloud.
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- [Configuration](/documentation/private-cloud/configuration/index.md) — Advanced configuration options for Private Cloud deployments.
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- [Backups](/documentation/private-cloud/backups/index.md) — Configure backup and restore for Private Cloud clusters.
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- [Logging & Monitoring](/documentation/private-cloud/logging-monitoring/index.md) — Set up observability for Private Cloud environments.
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- [API Reference](/documentation/private-cloud/api-reference/index.md) — Private Cloud management API reference.
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## Operations
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- [Configuration](/documentation/ops-configuration/index.md) — Customize Qdrant via config files and environment variables; runtime administration; GPU-accelerated 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; understand the background optimizer.
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## Security & Troubleshooting
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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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- [Troubleshooting](/documentation/common-errors/index.md) — Diagnose common runtime errors: open-file limits, filesystem incompatibilities, corrupted collection metadata.
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@@ -53,3 +53,26 @@ hideInSidebar: true
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build:
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render: always
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---
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# Explore the Qdrant Ecosystem
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## Migration
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- [Migration Tool](/documentation/migrate-to-qdrant/index.md) — Move vectors, payloads, and sparse embeddings from Chroma, Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, and OpenSearch.
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- [Migration Guidance](/documentation/migration-guidance/index.md) — Structured framework for verifying migrations and catching silent data and search regressions.
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- [Data Synchronization](/documentation/data-synchronization/index.md) — Keep Qdrant in sync with source databases using CDC, batch reindexing, or dual-write patterns for fresh search results.
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## Integrations
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- [Data Management](/documentation/data-management/index.md) — Connect Qdrant to ETL and streaming tools to ingest, transform, and sync vectors at scale.
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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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- [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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- [Observability](/documentation/observability/index.md) — Connect Qdrant to Datadog, OpenLIT, and OpenLLMetry to monitor performance and traces.
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- [Platforms](/documentation/platforms/index.md) — No-code and low-code integrations with n8n, Make, MuleSoft, Pipedream, Power Apps, and more.
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## Ecosystem Guides
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- [Essential Examples](/documentation/tutorials-build-essentials/index.md) — Hands-on tutorials for agentic RAG, multimodal search, data ingestion, and automation integrations.
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- [Build Prototypes](/documentation/examples/index.md) — End-to-end code samples for RAG pipelines, hybrid search, multitenancy, recommendations, and multimodal search.
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- [Improve Search](/documentation/improve-search/index.md) — Techniques for improving retrieval relevance and pipeline output quality.
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- [Practice Datasets](/documentation/datasets/index.md) — Ready-made Qdrant snapshots of public datasets you can import and explore without the embedding step.
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