Vertex AI Vector Search vs Zilliz Cloud

Vertex AI Vector Search9.2Visit Zilliz Cloud8.6Visit

Higher score Vertex AI Vector Search #2 in Vector Databases 9.2/10 Paid ✓ 3 of 3 features Visit Google Cloud

vs

Zilliz Cloud #8 in Vector Databases 8.6/10 Free plan · 30-day trial Free planFree trial✓ 3 of 3 features Visit Zilliz Cloud

• Vertex AI Vector Search fits best

  Google Cloud teams needing managed hybrid search

• Zilliz Cloud fits best

  Managed Milvus-compatible cloud deployments

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Side by side

Feature	Vertex AI Vector Search 9.2/10 Visit ↗	Zilliz Cloud 8.6/10 Visit ↗
At a glance
Editor score	9.2	8.6
Ranking	#2 in Vector Databases	#8 in Vector Databases
Best for	Google Cloud teams needing managed hybrid search	Managed Milvus-compatible cloud deployments
Pricing model	Paid	Free plan + paid
Starting price	Not checked yet	—
Free plan	Not checked yet	✓ (best)
Free trial	—	30 days
Deployment	Cloud	Cloud
Platforms	Web	Web
Support	Community, Docs	Docs
Built for	Enterprise	Small business, Mid-market, Enterprise
Features Vertex AI Vector Search 3/3 · Zilliz Cloud 3/3
Hybrid search	✓	✓
Metadata filtering	✓	✓
Sparse vectors	✓	✓
Specs
Deployment	Cloud	Cloud
Maximum dimensions	Not checked yet	32768 dimensions
Index types	Tree-AH, brute force	FLAT, IVF_FLAT, IVF_SQ8, IVF_PQ, HNSW, DISKANN, AUTOINDEX, SCANN, HNSW_SQ, HNSW_PQ, HNSW_PRQ, IVF_RABITQ, SPARSE_INVERTED_INDEX, SPARSE_WAND
SDK languages	Python, Java	Python, Java, Go, Node.js, C++
Our review
Pros	Supports dense, sparse, hybrid, and filtered vector search Offers batch and streaming index updates Provides public and private endpoints with SDK, REST, and gRPC access	Supports dense, sparse, binary, hybrid, and full-text search Includes filtering, reranking, backups, restore, and migration tools Offers SaaS and BYOC deployment with major cloud storage integrations
Cons	Usage-based costs span serving, building, and updating indexes Cloud deployment limits portability across infrastructure providers Requires Google Cloud services and client libraries for its ecosystem fit	Paid tiers use usage-based pricing rather than fixed subscription rates Cloud deployment may not suit teams seeking a self-hosted product Its broad feature set may exceed the needs of simple vector search projects
Our verdict	Vertex AI Vector Search is a managed cloud vector search engine from Google Cloud for semantic search, recommendations, and generative AI applications. It is aimed at teams that want to create, deploy, update, and query indexes through… Read the review →	Zilliz Cloud is a fully managed Milvus service for building and operating vector search applications. It is aimed at teams developing semantic search, retrieval-augmented generation, recommendations, and multimodal retrieval workloads… Read the review →

Strengths and trade-offs

• Vertex AI Vector Search — where it wins

  • Supports dense, sparse, hybrid, and filtered vector search
  • Offers batch and streaming index updates
  • Provides public and private endpoints with SDK, REST, and gRPC access

  Where it doesn't

  • Usage-based costs span serving, building, and updating indexes
  • Cloud deployment limits portability across infrastructure providers
  • Requires Google Cloud services and client libraries for its ecosystem fit

• Zilliz Cloud — where it wins

  • Supports dense, sparse, binary, hybrid, and full-text search
  • Includes filtering, reranking, backups, restore, and migration tools
  • Offers SaaS and BYOC deployment with major cloud storage integrations

  Where it doesn't

  • Paid tiers use usage-based pricing rather than fixed subscription rates
  • Cloud deployment may not suit teams seeking a self-hosted product
  • Its broad feature set may exceed the needs of simple vector search projects

• Vertex AI Vector Search9.2/10 · Paid

  A managed Google Cloud option for teams building dense, sparse, and hybrid search.

  Visit Google CloudFull verdict →
• Zilliz Cloud8.6/10 · Free plan · 30-day trial

  A capable managed vector database for teams building AI search applications.

  Visit Zilliz CloudFull verdict →