Aaron talks with Ovais Tariq, co-founder and CEO of Tigris Data and former Uber engineer who helped scale one of the world’s largest distributed systems. They discuss Uber’s hyperscale infrastructure, what it takes to build an S3-compatible object store from scratch, and how distributed storage is evolving for the AI era.

Follow Ovais:
Twitter: https://twitter.com/ovaistariq
LinkedIn: https://www.linkedin.com/in/ovaistariq
Tigris: https://www.tigrisdata.com

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Chapters:
00:00 - Introduction and overview of the episode
01:35 - Ovais’s background and introduction to Tigris
03:00 - Building distributed databases and infrastructure at Uber
06:00 - Uber’s in-house philosophy and massive data scale
09:00 - Hardware, power density, and talking to chip manufacturers
12:00 - Learning curve of scaling hardware and data centers
14:00 - The Halloween outage and lessons from Cassandra
16:00 - Building data centers across the world for Uber
17:00 - Founding Tigris and the vision for global storage
18:45 - How Tigris differs from AWS S3
20:00 - The architecture of Tigris: caching, metadata, and replication
32:00 - Why Tigris uses FoundationDB and its reliability
36:00 - Managing global and regional metadata
38:00 - How Tigris dynamically moves and caches data
41:30 - Building their own data centers and backbone
43:45 - Specialized storage for AI workloads
46:00 - Small file optimization and real-world use cases
49:00 - Snapshots, forking, and agentic AI workflows
51:00 - How AI transformed Tigris’s customer base
54:00 - Partnership with Fly.io and the distributed cloud ecosystem
57:00 - Growth, customers, and focus on media and AI companies
59:00 - What’s next for Tigris: distributed file system plans
1:01:00 - Technical challenges and building trust in durability
1:03:00 - Call to action: try Tigris and upcoming snapshot feature
1:05:00 - Advice for engineers leaving big companies to start something new
1:06:30 - Where to find Ovais online and closing remarks