Google Vertex AIPaid
Google Cloud's unified AI platform — access to Gemini and partner models, plus tools to build, deploy, and govern AI and agents.
AI Infrastructure comparison
Google Vertex AI vs Weaviate
Pricing, pros, cons, and ideal use cases — side by side.
WeaviateFreemium
An open-source vector database for production semantic search and RAG, available self-hosted or as a managed cloud service.
At a glance
| Google Vertex AI | Weaviate | |
|---|---|---|
| Pricing | PaidUsage-based pricing across model and platform services, billed through Google Cloud. | FreemiumOpen-source and free to self-host. Weaviate Cloud is a managed, usage-based service. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Enterprises already on Google CloudTeams wanting Gemini under enterprise governanceOrganizations consolidating the AI lifecycle on one platform | Teams building production RAG and semantic searchSaaS apps needing multi-tenant data isolationEnterprises wanting self-hosted or managed options |
Pros & cons
Google Vertex AI
Pros
- Gemini plus a broad Model Garden
- End-to-end build, deploy, evaluate, and govern
- Inside Google Cloud IAM and compliance
- Strong data and analytics integration
Cons
- Large, complex platform surface area
- Most valuable only if you are already on GCP
- Getting value requires real platform investment
Weaviate
Pros
- Mature open-source vector database
- Hybrid keyword-plus-vector search
- Multi-tenancy for isolating customer data
- Self-hosted or managed cloud
Cons
- Self-hosting carries an operational burden
- Retrieval quality still depends on your tuning
- Another datastore to run and monitor
Which should you choose?
Weaviate is the lighter-weight option (Freemium), while Google Vertex AI sits higher on the pricing ladder (Paid). Google Vertex AI is built around enterprises already on google cloud; Weaviate leans more toward teams building production rag and semantic search. Shortlist the one whose strengths line up with your biggest constraint.