Do I need to control where embeddings are stored?

Usually yes, if you care about privacy, cost, latency, or compliance.

When you should control embedding storage

You’ll want explicit control if any of these matter:

• Sensitive data: embeddings can still leak information about the source text.
• Compliance: you may need to keep data in a specific region, tenant, or encrypted store.
• Cost: large vector indexes can get expensive fast.
• Performance: choosing the right vector database / index affects retrieval speed.
• Lifecycle: you may need deletion, reindexing, versioning, or audit trails.

Common storage options

• Managed vector DB: easiest operationally, good for scaling.
• Self-managed database + vector extension: more control, more ops.
• Local/in-memory: fine for prototypes or small datasets.
• File/object storage: possible for offline batch processing, but not ideal for search.

Rule of thumb

• Prototype or toy app: not much control needed.
• Production app with user data: yes, you should decide exactly where embeddings live, who can access them, and how they’re deleted.

If you want, I can help you choose a storage approach based on your use case.