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SPECIFICTION
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Milvus vs Qdrant

Milvus

milvus.io

Qdrant

qdrant.tech

Side by side

FigureMilvusQdrant
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
Web—Yes
Windows—Yes
macOS—Yes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published15
Spec score · Ai Databases8.3 (#8)8.0 (#14)
Spec score · Vector Databases8.2 (#7)8.0 (#9)
Spec score · AI Search and Discovery Platforms Software8.1 (#9)7.8 (#14)
Spec score · Search Databases8.2 (#11)7.9 (#16)
Spec score · Search & Vector Database Platforms8.2 (#9)7.9 (#12)
Spec score · Database Software8.2 (#39)7.7 (#61)
DeploymentMilvus offers Lite as a Python library, Standalone as a single-machine server, and Distributed for Kubernetes clusters.Qdrant can be run locally using its Docker image or used through Qdrant Cloud.
Free planYesYes
IntegrationsThe integrations documentation lists tools including LangChain, LlamaIndex, Haystack, DSPy, Dify, Langflow, OpenAI, Cohere, and HuggingFace.Qdrant lists integrations including LangChain, LlamaIndex, Airbyte, Unstructured, DocArray, and AutoGen.
ProductMilvus is an open-source vector database built for GenAI applications.Qdrant is a vector similarity search engine with an API to store, search, and manage vectors with additional payload data.
SupportThe Milvus site lists community channels including Slack, Discord, GitHub, and Milvus Office Hours.The pricing page lists community support as Discord-only and paid support options with 10h/day business-hours or 24/7 coverage.

Plans

Milvus

  • Milvus (open-source software)Free

Milvus pricing →

Qdrant

  • Free TierFree
  • Hybrid CloudPriced on request
  • Premium TierPriced on request
  • Private CloudPriced on request
  • Standard TierPriced on request

Qdrant pricing →

In their own words

Milvus

Milvus is an open-source vector database from Zilliz for GenAI and scalable vector search. It supports approximate-nearest-neighbor, filtered, range, hybrid, and full-text search, along with reranking, fetch, and query operations. Metadata filtering, sparse vectors, and index types including HNSW, IVF, FLAT, DiskANN, and SCANN are documented. Deployment choices are Milvus Lite as a Python library, Standalone as a single-machine server, and Distributed on Kubernetes. Documentation recommends Lite for up to a few million vectors, Standalone up to 100 million, and Distributed for 100 million to tens of billions. Lite can run locally without a cloud service for private or sensitive data; an online upgrade from Standalone to a cluster is not currently supported. Official interfaces include REST plus Python, Go, Java, Node.js, and C++ APIs or SDKs. C# is contributed by Microsoft and Rust is under development. Security documentation covers authentication, TLS for gRPC and REST, and role-based access control at collection, database, and instance levels. The Apache 2.0 software is free, and Zilliz Cloud is offered as a managed option.

Visit milvus.io

Qdrant

Qdrant is a vector similarity search engine and API for storing, searching, and managing vectors with payload data. A point can pair a vector with JSON metadata that filters search results. It supports dense, sparse, and multivector configurations, plus hybrid retrieval that combines semantic and lexical search. These capabilities can serve semantic search and recommendation systems. Qdrant can run locally with its Docker image or through Qdrant Cloud. REST and gRPC APIs are available, along with official client libraries for Python, JavaScript/TypeScript, Rust, Go, .NET, and Java. Listed integrations include LangChain, LlamaIndex, Airbyte, Unstructured, DocArray, and AutoGen. The free cloud tier is intended for testing and prototypes, with a single-node cluster, 1GB RAM, and 4GB disk. Qdrant Cloud enables TLS and encryption at rest; self-hosted users must configure these controls, and authentication and encryption are off by default in self-hosted open-source deployments. Qdrant was founded in 2021 and is headquartered in Berlin, Germany.

Visit qdrant.tech