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Hunter Leath, CEO of Archil, explains how they’re building a “universal storage engine” that sits between your apps and S3—making an S3 bucket behave like a fast, POSIX-compatible disk for containers, servers, and even Lambda. Along the way, we dig into how their SSD-backed clusters and custom protocol avoid the usual small-file pain and where this approach shines (and where it doesn’t).
Follow Hunter:
Twitter/X: https://twitter.com/jhleath
Archil Twitter/X: https://twitter.com/archildata
Archil: https://archil.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 - Intro: Archil Data and “S3 as a disk”
01:05 - Hunter’s background and the core pitch
02:32 - The real problem: state management (S3 vs block storage)
05:02 - SQLite on S3: what the stack looks like
07:13 - The missing layer: durable SSD-backed clusters
10:14 - Who uses this: unstructured data, CI/CD, Git, agents
12:15 - Small files + Git performance and avoiding S3 request explosion
16:22 - Why they built a new protocol (NFS vs Luster)
20:00 - What gets written to S3: real files in your bucket
22:29 - S3 limits, throttling, and the “keep it on SSD” escape hatch
25:32 - Multi-cloud + R2, and why regions/latency matter
32:10 - Pricing model: “pay only when data is active”
34:41 - Tradeoffs: random reads and ultra-low-latency metal
37:19 - Storage/compute separation and AI/agent-native workflows
43:21 - YC timeline + the marketing challenge of a “universal layer”
47:34 - Single-tenant clusters for enterprises and why it’s hard
50:27 - Where the company is now, hiring, and how to try it (disk.new)
By Try Hard Studios5
33 ratings
Hunter Leath, CEO of Archil, explains how they’re building a “universal storage engine” that sits between your apps and S3—making an S3 bucket behave like a fast, POSIX-compatible disk for containers, servers, and even Lambda. Along the way, we dig into how their SSD-backed clusters and custom protocol avoid the usual small-file pain and where this approach shines (and where it doesn’t).
Follow Hunter:
Twitter/X: https://twitter.com/jhleath
Archil Twitter/X: https://twitter.com/archildata
Archil: https://archil.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 - Intro: Archil Data and “S3 as a disk”
01:05 - Hunter’s background and the core pitch
02:32 - The real problem: state management (S3 vs block storage)
05:02 - SQLite on S3: what the stack looks like
07:13 - The missing layer: durable SSD-backed clusters
10:14 - Who uses this: unstructured data, CI/CD, Git, agents
12:15 - Small files + Git performance and avoiding S3 request explosion
16:22 - Why they built a new protocol (NFS vs Luster)
20:00 - What gets written to S3: real files in your bucket
22:29 - S3 limits, throttling, and the “keep it on SSD” escape hatch
25:32 - Multi-cloud + R2, and why regions/latency matter
32:10 - Pricing model: “pay only when data is active”
34:41 - Tradeoffs: random reads and ultra-low-latency metal
37:19 - Storage/compute separation and AI/agent-native workflows
43:21 - YC timeline + the marketing challenge of a “universal layer”
47:34 - Single-tenant clusters for enterprises and why it’s hard
50:27 - Where the company is now, hiring, and how to try it (disk.new)

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