Vector Search | Convex Developer Hub
I'm a prospective Convex customer needing clarification on vector storage pricing. The tooltip for vector storage on the pricing page says:
"Includes the size of any vectors within a document that are stored in a vector index."
And in the Professional plan, the tooltip says "Then $10 per GB".
1) What exactly is being measured in GB? A literal interpretation is that the data in vectorized form is measured and billed. But is it really $10/GB for vector data?
2) Which technique does Convex use (or encourage the user to use) to convert business text data to vectors? I only found this in the docs:
If you're using embeddings, this dimension should match the size of your embeddings (e.g. 1536 for OpenAI).
https://docs.convex.dev/vector-search
3) Any general advice on how a Convex customer should forecast vector storage billing costs for a given business text data? For most customers, is it essentially forecasting the space needed for OpenAI embeddings? This seems like the most important financial planning task for a Convex customer with significant vector searching in the app.
"Includes the size of any vectors within a document that are stored in a vector index."
And in the Professional plan, the tooltip says "Then $10 per GB".
1) What exactly is being measured in GB? A literal interpretation is that the data in vectorized form is measured and billed. But is it really $10/GB for vector data?
2) Which technique does Convex use (or encourage the user to use) to convert business text data to vectors? I only found this in the docs:
If you're using embeddings, this dimension should match the size of your embeddings (e.g. 1536 for OpenAI).
https://docs.convex.dev/vector-search
3) Any general advice on how a Convex customer should forecast vector storage billing costs for a given business text data? For most customers, is it essentially forecasting the space needed for OpenAI embeddings? This seems like the most important financial planning task for a Convex customer with significant vector searching in the app.
