Skip to main content
Introducing Respan Router

Milvus vs Weaviate (2026)

Updated February 28, 2026

vs

Overview

Rating
10.0 / 10
Rating
10.0 / 10
Best For
Organizations that need vector search at billion-scale with high throughput
Best For
Developers who need a flexible, open-source vector database with multimodal and hybrid search
Product Summary

Milvus is an open-source vector database built for scalable similarity search, capable of handling billions of vectors. Backed by the Zilliz company, Milvus supports multiple index types (IVF, HNSW, DiskANN), GPU-accelerated search, and multi-tenancy. Zilliz Cloud offers a fully managed version with automatic scaling. Milvus is widely used in enterprise deployments requiring high-throughput vector search at scale.

Product Summary

Weaviate is an open-source vector database that combines vector search with structured filtering and generative capabilities. It supports multiple vectorization modules, hybrid search (combining BM25 and vector search), and built-in integrations with LLMs for retrieval-augmented generation. Weaviate offers both self-hosted and managed cloud deployments, with a GraphQL API that makes it easy to query complex data structures.

Starting Price
Free
Starting Price
Open Source
Free Trial
Yes
Free Trial
No
Free Version
Yes
Free Version
No
Website

Key features

Core capabilities each platform advertises.

MilvusMilvus
  • Billion-scale vector search
  • GPU-accelerated indexing
  • Distributed architecture
  • Multiple index types
  • Cloud and self-hosted options
WeaviateWeaviate
  • Open-source vector database
  • Hybrid search (vector + keyword)
  • Multi-modal support
  • GraphQL and REST APIs
  • Kubernetes-native deployment

Strengths and tradeoffs

What each tool does well, and the limitations to keep in mind.

MilvusMilvus

Pros

  • Extreme scalability handling billions of vectors in distributed environments
  • Fully open-source under Apache 2.0 with no vendor lock-in
  • Hybrid search combining dense and sparse vectors in single queries
  • Rich index flexibility with IVF, HNSW, DiskANN and GPU acceleration
  • Managed cloud option reduces DevOps burden with auto-scaling

Cons

  • Complex distributed architecture requiring Kubernetes for production
  • Steep learning curve for index tuning and deployment configuration
  • High memory and storage requirements for large datasets
  • No in-place vector updates requiring delete and re-insert workarounds

Milvus or Weaviate — which should you choose?

Choose Milvus if you want

  • Billion-vector similarity search
  • Large-scale recommendation systems
  • Image and video retrieval
  • Genomics and scientific computing
  • Enterprise-scale RAG systems

Choose Weaviate if you want

  • Multimodal search across text, images, and more
  • RAG with hybrid retrieval
  • E-commerce product search
  • Content recommendation engines
  • Self-hosted vector search

Compare Milvus and Weaviate on your own traffic

10KFree traces/mo
1,000+Models
5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Frequently Asked Questions

Other popular comparisons