Building serverless vector search with Turbopuffer CEO, Simon Eskildsen
Database School13 Marras 2025

Building serverless vector search with Turbopuffer CEO, Simon Eskildsen

In this episode, Aaron Francis talks with Simon Eskildsen, co-founder and CEO of TurboPuffer, about building a high-performance search engine and database that runs entirely on object storage. They dive deep on Simon's time as an engineer at Shopify, database design trade-offs, and how TurboPuffer powers modern AI workloads like Cursor and Notion.

Follow Simon:
Twitter: https://twitter.com/Sirupsen
LinkedIn: https://ca.linkedin.com/in/sirupsen
Turbopuffer: https://turbopuffer.com

Follow Aaron:
Twitter/X: https://twitter.com/aarondfrancis
Database School: https://databaseschool.com
Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)
LinkedIn: https://www.linkedin.com/in/aarondfrancis
Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.

Chapters
00:00 - Introduction
01:11 - Simon’s background and time at Shopify
03:01 - The Rails glory days and early developer experiences
04:55 - From PHP to Rails and joining Shopify
06:14 - The viral blog post that led to Shopify
09:03 - Discovering engineering talent through GitHub
10:06 - Scaling Shopify’s infrastructure to millions of requests per second
12:47 - Lessons from hypergrowth and burnout
14:46 - Life after Shopify and “angel engineering”
16:31 - The Readwise problem and discovering vector embeddings
18:22 - The high cost of vector databases and napkin math
19:14 - Building TurboPuffer on object storage
21:20 - Landing Cursor as the first big customer
23:00 - What TurboPuffer actually is
25:26 - Why object storage now works for databases
28:37 - How TurboPuffer stores and retrieves data
31:06 - What’s inside those S3 files
33:02 - Explaining vectors and embeddings
35:55 - How TurboPuffer v1 handled search
38:00 - Transitioning from search engine to database
44:09 - How Turbopuffer v2 and v3 improved performance
47:00 - Smart caching and architecture optimizations
49:04 - Trade-offs: high write latency and cold queries
51:03 - Cache warming and primitives
52:25 - Comparing object storage providers (AWS, GCP, Azure)
55:02 - Building a multi-cloud S3-compatible client
57:11 - Who TurboPuffer serves and the scale it runs at
59:31 - Connecting data to AI and the global vision
1:00:15 - Company size, scale, and hiring
1:01:36 - Roadmap and what’s next for TurboPuffer
1:03:10 - Why you should (or shouldn’t) use TurboPuffer
1:05:15 - Closing thoughts and where to find Simon

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