Tag: real time
Episode 469: Dhruba Borthakur on Embedding Real-time Analytics in Applications
Dhruba Borthakur, CTO and co-founder of Rockset, discusses the core requirements of real-time analytics, how it differs from traditional analytics, and the use cases that benefit from it. Host Kanchan Shringi spoke with Dhruba about the evolution from Batch to streaming to real-time analytics and the relation to big data. They also explored how people […]
SE-Radio Episode 349: Gary Rennie on Phoenix
Gary Rennie, a core contributor to Phoenix and Plug, discusses the Phoenix, a web framework for the Elixir programming language. Host Nate Black talks with Gary about why companies use Phoenix and what they use it for, how to write a Phoenix application, how the subsystems of Phoenix work together, and how to troubleshoot performance […]
SE-Radio Episode 233: Fangjin Yang on OLAP and the Druid Real-Time Analytical Data Store
Fangjin Yang, creator of the Druid real-time analytical database, talks with Robert Blumen. They discuss the OLAP (online analytical processing) domain, OLAP concepts (hypercube, dimension, metric, and pivot), types of OLAP queries (roll-up, drill-down, and slicing and dicing), use cases for OLAP by organizations, the OLAP store’s position in the enterprise workflow, what “real time” […]
Episode 73: Real Time Systems with Bruce Powel Douglass
This episode is a conversation with Bruce Powel Douglass on real time systems. We started by discussing what real time software is, and explored the difference between hard and soft real time. We then looked at different scheduling strategies, and the meaning of terms like urgency and importance in the context of scheduling. Next was a discussion of typical architectural styles for real time systems and how architectures are described in this context. This led us to a discussion about the importance of modeling, formalisms and languages as well as the role of automatic code generation from those models. We then looked at how to model QoS aspects and the role of SysML for modeling real time systems. We then had a brief look at which programming languages are used these days for real time systems and the role of static analysis to determine various properties of those programs in advance. The last part of the discussion focused on some best practices for building real time systems, the challenges in distributed real time systems and how real time systems can be tested effectively.
