What AI says about Qdrant
Qdrant is an open-source vector search engine and database available on-premise and through Qdrant Cloud. It is among the brands most often named when buyers seek low-latency production vector search, advanced metadata filtering, and open-source deployment without a cloud subscription.
AI calls ithigh-performance,written in rust,open-source,fast,efficient,lightweight
Since Jul 5Updated Nov 10, 2026Based on 19,459 AI answers
Reviewed by Dimitry Apollonsky
Mentioned in · Public index
11%
of AI answers about Qdrant and its rivals · since Jul 5
Based on 19,459 AI answers
- ChatGPT11%
- Google AI Mode11%
How often AI mentions Qdrant
of AI answers about Qdrant and its rivals
Track your brand free to see 13 weeks of history.
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Sep 14OctNov 2
- · ChatGPT switched to GPT-6 Luna
Qdrant products in AI answers
BrandMentioned in
Markets where AI mentions Qdrant
Mentioned inLowHighFew answers
All marketsChatGPTGoogle AI Mode
- Developer Backend & Vector Search ServicesChatGPTGoogle AI Mode
- Vector Database PlatformsChatGPTGoogle AI Mode
- Visual Search and Auto-Tagging APIsChatGPTGoogle AI Mode
- Product Search and Discovery PlatformsChatGPTGoogle AI Mode
- RAG Platforms and Retrieval ToolsChatGPTGoogle AI Mode
- LLM Security and Governance PlatformsChatGPTGoogle AI Mode
- Embedding Model APIs and ServicesChatGPTGoogle AI Mode
- LLM Fine-Tuning and Hosting PlatformsOutside both engines’ top 25
- Enterprise MLOps Model Registry PlatformsOutside both engines’ top 25
- AI Document Processing and OCR ToolsOutside both engines’ top 25
- AI Knowledge Base Assistant BotsOutside both engines’ top 25
- AI Knowledge Graph PlatformsOutside both engines’ top 25
Topics where AI mentions Qdrant
TopicMentioned in · on this topicRank
- Hybrid vector and keyword search
- Multimodal vector search
- Vector database for generative AI
- In-memory vector database without SSD
- Vector-based recommendation AI for conversion
- Image similarity search APIs
- Local development prototyping
- Multi-tenant vector isolation
- Hosted embeddings with tenant isolation
- Visual search API with custom embedding support
- Multimodal embedding storage and query
- High-performance API development
- Managed vector databases for production RAG
- Managed embedding generation
- Document parsing for LLM pipelines
- Vector databases with metadata filtering
- RAG pipeline development platform
- Self-hosted open-source RAG framework
- Backend as a service with vector search
- Embedding model management and deployment
- Dynamic tool discovery
- Scalable unstructured data processing for legacy file servers
- Open-source embedding models
- End-to-end RAG platform with ingestion and vectorization
- RAG retrieval visualization tool
- Zero-retention RAG platform for trade secrets
- Semantic product search
- Managed embedding APIs
- Advanced RAG retrieval strategies
- RAG document reranking
- Self-hosted open-source LLM management platform
- Agent memory integration
- In-warehouse generative AI
- Coding assistant with private repository grounding
- Developer onboarding assistance
- Conversational AI agent framework
- Web research agent frameworks
- Managed enterprise RAG platform
- API-first AI customer support bot builder
- Enterprise LLM fine-tuning and RAG
- Internal knowledge Q&A and search
- Conversational AI chatbot development
- LLM-based document analysis
- LLM knowledge graph databases
- LLM integration into existing applications
- Enterprise RAG and fine-tuning
- Multi-agent orchestration
- Supervised AI tutoring
- PII redaction for LLM pipelines
QuestionAI picks mostMentioned in
Qdrant in AI answers
1 of 8
My goal is to find an efficient way to store and query multimodal embeddings (text + image). Which vector database has the best multimodal support?
ChatGPTChatGPT· Nov 8, 2026
Qdrant is the best overall starting point for a production text-and-image embedding system.
Google AI ModeGoogle AI Mode· Nov 8, 2026
Qdrant is famously memory-efficient and features payload (metadata) indexing that is deeply integrated with vector search.
Sites AI cites
- Your site33%
- Qdrant - Vector Search Engine (opens in a new tab) · 6%Leaves Qdrant out
- Documentation - Qdrant (opens in a new tab) · 2%Leaves Qdrant out
- Vector Search Benchmarks - Qdrant (opens in a new tab) · 2%Lists Qdrant
- Hybrid Search - Qdrant (opens in a new tab) · 1%Lists Qdrant
- Hybrid Queries - Qdrant (opens in a new tab) · 1%Lists Qdrant
- Filtering - Qdrant (opens in a new tab) · 1%Lists Qdrant
- Distributed Deployment - Qdrant (opens in a new tab) · 1%Lists Qdrant
- AI-Powered Vector Search for Smarter Shopping & Personalized E-Commerce - Qdrant (opens in a new tab) · 1%
- Indexing - Qdrant (opens in a new tab) · 1%Lists Qdrant
- Collections - Qdrant (opens in a new tab) · 1%Lists Qdrant
- Lists Qdrant on 4 of 4 pages5%
- Medium (opens in a new tab) · 1%Lists Qdrant
- Medium (opens in a new tab) · <1%Lists Qdrant
- Top Vector Databases — 2024 | Production-Grade | by Mudassir Aqeel Ahmed (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%Lists Qdrant
- Medium (opens in a new tab) · <1%Lists Qdrant
- Vector Databases for RAG - by Gur Raunaq Singh - Medium (opens in a new tab) · <1%
- Which Vector Database Should You Use? Choosing the Best One for Your Needs | by Plaban Nayak | The AI Forum | Medium (opens in a new tab) · <1%
- Vector Databases Explained: The Missing Piece in Your AI Stack (opens in a new tab) · <1%
- Azure AI Search, Qdrant, Cosmos DB & pgvector - Medium (opens in a new tab) · <1%
- The Hidden Bottleneck of RAG: Why Your Vector Database is Crashing Your Pipeline (opens in a new tab) · <1%
- Lists Qdrant on 1 of 1 page5%
- 15. Pinecone vs. Weaviate vs. Milvus vs. Qdrant (opens in a new tab) · <1%
- 6 Vector Databases Compared: Which One Should You Use? (opens in a new tab) · <1%
- Vector Databases: From First Principles to Production (2026 ... (opens in a new tab) · <1%
- Top 15 Vector Databases for AI Builders in 2026 | Pinecone, Milvus, Qdrant, Chroma & More (opens in a new tab) · <1%Lists Qdrant
- 15. Pinecone vs. Weaviate vs. Milvus vs. Qdrant (opens in a new tab) · <1%
- Is Your Vector Database Really Fast? (opens in a new tab) · <1%
- Vector Databases Explained: The Complete Guide for 2026 (opens in a new tab) · <1%
- Vector Database Comparison: Qdrant vs Milvus vs Weaviate + PostgreSQL with pgai (opens in a new tab) · <1%
- Qdrant Essentials | Implementing Hybrid Search in Qdrant: Merging Dense & Sparse Vectors (opens in a new tab) · <1%
- Vector Databases Explained: The Complete Guide for 2026 (opens in a new tab) · <1%
- Leaves Qdrant out5%
- Lists Qdrant on 1 of 1 page3%
- Lists Qdrant on 3 of 3 pages2%
- GitHub - qdrant/qdrant: Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ · GitHub (opens in a new tab) · 1%Lists Qdrant
- Best way for indexing a stream of data. · qdrant · Discussion #67 · GitHub (opens in a new tab) · <1%Lists Qdrant
- JWT RBAC payload filters - documentation needed · qdrant · Discussion #7987 · GitHub (opens in a new tab) · <1%Lists Qdrant
- qdrant repositories · GitHub (opens in a new tab) · <1%
- devrel-projects/qdrant-bench-suite/README.md at main · qdrant-labs/devrel-projects · GitHub (opens in a new tab) · <1%
- Adding TTL support · Issue #8236 · qdrant/qdrant - GitHub (opens in a new tab) · <1%
- GitHub - VersionAI/qdrant-vectorial-db: Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ · GitHub (opens in a new tab) · <1%
- GitHub - mcpuishor/qdrant-laravel: A fluent package to interact with ... (opens in a new tab) · <1%
- openai-knowledge-retrieval/README.md at main · openai/openai-knowledge-retrieval · GitHub (opens in a new tab) · <1%
- What storage does qdrant use? FAISS or something else? What persistence storage does qdrant? · qdrant · Discussion #2540 · GitHub (opens in a new tab) · <1%
- Lists Qdrant on 3 of 3 pages2%
- Lists Qdrant on 1 of 1 page2%
- 1%
- Vector Databases in Practice: Building a Realistic Hybrid Search RAG System with Qdrant (opens in a new tab) · 1%
- Medium (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%
- 10 Underground AI/ML Tools That Actually 100x Developer Productivity | by Rohan Mistry | Towards AI (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%
- Building a Modern RAG Agent in 2026: Qwen3 Embeddings and Vector Database in Qdrant. (opens in a new tab) · <1%
- Setting Up Your Qdrant Vector Database | by Harpreet Sahota (opens in a new tab) · <1%
- The 10 Best Vector Databases for RAG (opens in a new tab) · <1%
