Turbopuffer with Simon Hørup Eskildsen

Vector search has become a foundational technology for AI applications, enabling everything from semantic code search to contextual retrieval for large language models. However, a major challenge with vector databases has been the cost as data storage scales.

Turbopuffer is a vector database that focuses on speed, cost and scalability. It was created by Simon Hørup Eskildsen and Justin Li in 2023 and has seen adoption from high-profile companies such as Cursor and Notion.

Simon joins the podcast with Gregor Vand to discuss the origin of turbopuffer, its unique technical design, the economics of vector storage, and more.