Updated May 13, 2026 · Independent Analysis
Only in Milvus / Zilliz Cloud
- ✦ Distributed Architecture
- ✦ Billion-Scale Vectors
- ✦ ANNS Algorithms (HNSW, IVF, DiskANN)
✓ Free plan5k+ users · est. 2017
Only in Weaviate
- ✦ Hybrid Search (BM25 + Vector)
- ✦ Multimodal Support
- ✦ GraphQL API
✓ Free plan5k+ users · est. 2019
Pricing Intelligence

Milvus / Zilliz Cloud Plans
Free tier available
Milvus Open Source0
Open Source- • Full features
- • Apache 2.0
- • Community support
Zilliz Cloud Serverless
Custom- • From $0.1/CU-hr
- • Managed Milvus
- • Auto-scaling
- • Dedicated clusters
- • SLA
- • Private VPC
Full Milvus / Zilliz Cloud Pricing Breakdown →
Weaviate Plans
Free tier available
- • Full features
- • Community support
- • Apache 2.0
- • From $0.045/1M vectors
- • Managed cloud
- • No ops overhead
Enterprise Dedicated
Custom- • Custom deployment
- • SLA
- • Dedicated support
Full Weaviate Pricing Breakdown →Feature Matrix
1 differences found across 10 standardized features
Feature
Milvus / Zilliz Cloud
Weaviate
Pros & Cons Face-Off
Evaluative strengths and weaknesses — not feature lists
Pros
- +CNCF project — battle-tested for billion-scale workloads
- +GPU acceleration and DiskANN for cost-efficient large-scale search
- +Distributed architecture with independent storage/compute scaling
- +Multi-vector search supports complex AI use cases
Cons
- −Operational complexity — requires Kubernetes expertise for self-hosted
- −Overkill for small-scale RAG applications
Pros
- +Open source with managed cloud option gives deployment flexibility
- +Built-in vectorizers reduce pipeline complexity
- +Knowledge graph cross-references unique in category
- +Active community and excellent documentation
Cons
- −GraphQL API has steeper learning curve
- −Performance benchmarks trail Qdrant at very high scale
At a Glance
Starting PricePay-per-usevsPay-per-use
Feature Count16 featuresvs16 features
Frequently Asked Questions