When building AI applications with Weaviate, good early architectural decisions can aid future development velocity. Some choices are expensive to change later - like vectorization strategies and schema design - while others can be adjusted as you scale.

This guide focuses on the "when" and "why" behind different architectural choices, organized as actionable decision patterns you can apply to your specific use case.

Database-level decisions

Database-level decisions affect your entire deployment and are among the hardest to change later. These choices determine operational overhead, scalability, and feature availability.

Deployment type

Weaviate's functionality is identical across deployment options; the key difference is operational overhead.

If you want self-service deployment → Use Serverless Cloud

• All operational tasks managed through web console
• Example: Startup focused on product development, not infrastructure

If you need Weaviate Agents → Use Serverless Cloud or Enterprise Cloud

• Weaviate Agents are predefined workflows available only on Serverless & Enterprise Cloud
• Example: Natural language query interface without custom development

If you have a large dataset, or high throughput requirements → Consider Enterprise Cloud

• Enterprise Cloud is much better suited for provisioning, custom, larger resources
• Example: SaaS company experiencing healthy growth and considering next steps

If you want a bespoke, but managed solution → Use Enterprise Cloud

• Tailored deployment with custom configurations, managed by Weaviate
• Example: Large enterprise with specific networking, security, or compliance needs

If you must have full control, have DevOps capacity and resources → Consider Self-hosting

• You manage everything - infrastructure provisioning, updates, scaling, monitoring, disaster recovery, etc.
• Example: Where air-gapped environments are a must, or no external party involvement allowable

Learn more

• Installation: Deploying Weaviate

What's next?

Once you've chosen your deployment type, you need to plan how your database will scale as your data and usage grow.