landing_page/qdrant-landing/content/documentation/ecosystem-tab.md

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Explore the Qdrant Ecosystem	Explore the Qdrant ecosystem of integrations, partners, frameworks, and community tools built around vector search.	Discover the Qdrant ecosystem — integrations with frameworks, embedding providers, cloud platforms, and community-built tools for vector search.	ecosystem	/documentation/build/	false	partial title description image startedButton documentation/banners/banner-c Explore the Qdrant Ecosystem Dev-portal Ecosystem src alt /img/dev-portal-build/spanish-ai-app-hero.png Spanish AI app.png text url Get Started https://qdrant.to/cloud partial title description cardsPartial cards documentation/sections/cards-section Start Building Deploy and manage high-performance vector search clusters across cloud environments. Easily scale with fully managed cloud solutions, integrate seamlessly across hybrid setups, or maintain complete control with private cloud deployments in Kubernetes. documentation/cards/docs-cards id image title description link 1 src alt /img/dev-portal-build/search.png Search Search Build a simple neural search service with Qdrant and FastEmbed. Learn how to upload data, create indexes, and run search queries. url text /documentation/tutorials-develop/hybrid-search-fastembed/ Read More id image title description link 2 src alt /img/dev-portal-build/rag.png RAG RAG Build end-to-end prototype chatbots. Learn how Qdrant integrates with popular RAG frameworks like LangChain and LlamaIndex. url text /documentation/frameworks/langchain/ Read More id image title description link 3 src alt /img/dev-portal-build/pipelines.png Pipelines Pipelines Integrate Qdrant into your data infrastructure by connecting with popular data engineering tools. url text /documentation/send-data/ Read More	ecosystem	true	render always

Explore the Qdrant Ecosystem

Migration

• Migration Tool — Move vectors, payloads, and sparse embeddings from Chroma, Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, and OpenSearch.
• Migration Guidance — Structured framework for verifying migrations and catching silent data and search regressions.
• Data Synchronization — Keep Qdrant in sync with source databases using CDC, batch reindexing, or dual-write patterns for fresh search results.

Integrations

• Data Management — Connect Qdrant to ETL and streaming tools to ingest, transform, and sync vectors at scale.
• Embedding Providers — Connect to 30+ providers: OpenAI, Cohere, Jina, Mistral, AWS Bedrock, Voyage AI, Ollama, and more.
• Frameworks — Integrations with 40+ AI agent and RAG frameworks: LangChain, LlamaIndex, Haystack, CrewAI, AutoGen, Spring AI, and more.
• Observability — Connect Qdrant to Datadog, OpenLIT, and OpenLLMetry to monitor performance and traces.
• Platforms — No-code and low-code integrations with n8n, Make, MuleSoft, Pipedream, Power Apps, and more.

Ecosystem Guides

• Essential Examples — Hands-on tutorials for agentic RAG, multimodal search, data ingestion, and automation integrations.
• Build Prototypes — End-to-end code samples for RAG pipelines, hybrid search, multitenancy, recommendations, and multimodal search.
• Search Evaluation — Techniques for improving retrieval relevance and pipeline output quality.
• Practice Datasets — Ready-made Qdrant snapshots of public datasets you can import and explore without the embedding step.