RAG With Autoscaling: Better Performance With Lower Costs For pgvector
Blog post from Neon
Neon's autoscaling feature dynamically extends memory for HNSW index build operations, improving performance while reducing costs. This is particularly useful for applications that require vector similarity searches and Retrieval-Augmented Generation (RAG) apps. By allowing Postgres instances to scale up during high memory and CPU demands, Neon ensures optimal performance without constant overprovisioning. Autoscaling is available in all pricing plans and can be used with the free account.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 6 | 2,074 | 267 | 89 | +26% |
| RAG | 5 | 2,399 | 253 | 69 | +46% |
| LLM | 1 | 3,629 | 397 | 137 | -13% |
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