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Vertex AI Vector Search
What it is
Vertex AI Vector Search is a cloud vector search engine for semantic search, recommendations, retrieval-augmented generation, chatbots, and multimodal search. It uses Google Research’s ScaNN algorithm and supports dense embeddings, sparse embeddings, and hybrid search that combines semantic and keyword methods. Numeric and text-attribute filters can narrow results. Indexes can run at public or private endpoints, including Private Service Connect setups that provide private access from multiple user VPC networks. Google documents integrations with RAG Engine, Cloud Storage, Cloud Run, TensorFlow Recommenders, and LlamaIndex, plus Python and Java clients, a Python SDK, and REST workflows. Security controls include VPC Service Controls and customer-managed encryption keys. The paid service has a free trial, including potential $300 in Google Cloud credits for new customers. Usage billing covers serving, index building, updates, and streaming inserts, with rates varying by machine type and region.
For and against
For
- Dense, sparse, and hybrid search modes
- Numeric and text-attribute filtering
- Public or private index endpoints
- Python and Java client options
- Integrations with RAG and data tools
Against
- Paid usage-based billing
- Regional quotas limit index resources
- Cloud deployment only
The verdict
Vertex AI Vector Search combines several vector-search modes, filtering, private connectivity, and documented integrations. Review usage charges and regional quotas before planning a deployment.
Who it suits
It suits teams building search, recommendation, generative AI, chatbot, or multimodal applications through cloud APIs. It is also relevant for organizations needing private endpoints, filtering, documented SDKs, or Google Cloud security controls.
Plans and prices
Vertex AI Vector Search
price varies by machine type and region · build/update data processed: $3.00/GiB in all regions · streaming inserts: $0.45/GiB
Read 8 Oct 2026 · cloud.google.com
On the record
- APIs and SDKs
- The documentation links Python and Java clients, the Python SDK, and REST API workflows.cloud.google.com · read 8 Oct 2026
- Compliance
- Google’s compliance scope page lists Vector Search under Gemini Enterprise Agent Platform as under DISA review for DoD IL4 and IL5.docs.cloud.google.com · read 8 Oct 2026
- Endpoints
- Users can deploy an index to a public or private endpoint, including Private Service Connect configurations.docs.cloud.google.com · read 8 Oct 2026
- Filtering
- Searches can be restricted using numeric filtering and text attribute filtering.docs.cloud.google.com · read 8 Oct 2026
- Integrations
- Google documents use of Vector Search with RAG Engine, Cloud Storage, Cloud Run, TensorFlow Recommenders, and LlamaIndex.cloud.google.com · read 8 Oct 2026
- Intended use
- Google describes use cases including semantic search, recommendations, retrieval-augmented generation, chatbots, and multimodal search.cloud.google.com · read 8 Oct 2026
- Limits
- Per region and project, quotas include 5 concurrent index creations, 5 concurrent index updates, 50 deployed index nodes, and 100 indexes.docs.cloud.google.com · read 8 Oct 2026
- Private connectivity
- Private Service Connect supports private access to serving backends from multiple user VPC networks.docs.cloud.google.com · read 8 Oct 2026
- Purpose
- Vector Search is a vector search engine using Google Research’s ScaNN algorithm for search, recommendations, and generative AI applications.cloud.google.com · read 8 Oct 2026
- Search modes
- It supports dense embeddings, sparse embeddings, and hybrid search combining semantic and keyword search.docs.cloud.google.com · read 8 Oct 2026
- Security
- Vector Search supports VPC Service Controls and customer-managed encryption keys, among other Google Cloud security controls.cloud.google.com · read 8 Oct 2026
- Support
- Google provides support guidance for Vector Search and directs users to include diagnostic details when reporting problems.docs.cloud.google.com · read 8 Oct 2026
- Trial credits
- The overview page states that new Google Cloud customers can receive $300 in free credits to try Google Cloud products.cloud.google.com · read 8 Oct 2026
