All Episodes

Episode 182

March 20, 2024

with Kevin Liu

 – Software Engineer, Stripe

This week on The Data Stack Show, Eric and Kostas chat with Kevin Liu, Software Engineer at Stripe. During the episode, Kevin discusses data infrastructure challenges and the development of data products. He also shares insights on the importance of metadata management and the role of catalogs in maintaining data consistency across various systems. The conversation also covers open-source projects like the Python Iceberg library and the future of databases in the cloud, the ease of use of internal tools, the integration of data for builders, the balance between simplicity and functionality in user interfaces, and more.

Episode 181

March 13, 2024

with Mike Driscoll

 – CEO, Rill Data

This week on The Data Stack Show, Eric and Kostas chat with Mike Driscoll, the CEO of Rill Data. During the episode, Mike recounts his journey from the Human Genome Project to developing the Druid engine, which was created to handle massive advertising data. He discusses Druid’s adoption by major companies and its evolution, emphasizing the importance of speed, simplicity, and scalability in data tools. The dialogue covers the progression of BI tools, the role of object stores, and the integration of AI in data technology. Mike also touches on the significance of SQL and AI’s influence on data visualization, what he would do if he wasn’t working in data, and more.

Episode 180

March 6, 2024

with Kunal Agarwal

 – Co-Founder and CEO, Unravel Data

This week on The Data Stack Show, Eric and Kostas chat with Kunal Agarwal, the Co-Founder and CEO of Unravel Data. During the episode, Kunal discusses the evolution of data operations and the role of Unravel in simplifying these processes. The group discusses the shift towards real-time workloads, the impact of AI and machine learning, and the challenges of cloud migration and managing complex data environments. Kunal shares his journey from fashion to data management and emphasizes the importance of observability for data ops teams. The conversation also covers cost optimization, the productivity of data teams, reliability of data systems, the unique cost management considerations in cloud versus on-premises setups, and more.