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.

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. 

This week on The Data Stack Show, Eric and Kostas chat with Tony Wang, Graduate Research Assistant (PhD) at Stanford University. During the episode, Tony discusses his journey from China to studying electrical and hardware engineering at MIT, his transition to data processing systems for his Ph.D., and the academic-industry connection. Tony shares insights on cloud data processing, the limitations of academic hardware projects compared to industry giants like NVIDIA, and the potential for software innovation in academia. He also delves into his current research focus on time series data management, the challenges of integrating different data systems, the goal of improving data processing efficiency, the sales aspect of his research, and more.