Yelp needs to be able to consume and process all of the user interactions that happen in their platform in as close to real-time as possible. To achieve that goal they embarked on a journey to refactor their monolithic architecture to be more modular and modern, and then they open sourced it! In this episode Justin Cunningham joins me to discuss the decisions they made and the lessons they learned in the process, including what worked, what didn’t, and what he would do differently if he was starting over today.
If you like the features of Cassandra DB but wish it ran faster with fewer resources then ScyllaDB is the answer you have been looking for. In this episode Eyal Gutkind explains how Scylla was created and how it differentiates itself in the crowded database market.
What exactly is data engineering? How has it evolved in recent years and where is it going? How do you get started in the field? In this episode, Maxime Beauchemin joins me to discuss these questions and more.
There is a vast constellation of tools and platforms for processing and analyzing your data. In this episode Matthew Rocklin talks about how Dask fills the gap between a task oriented workflow tool and an in memory processing framework, and how it brings the power of Python to bear on the problem of big data.
Do you wish that you could track the changes in your data the same way that you track the changes in your code? Pachyderm is a platform for building a data lake with a versioned file system. It also lets you use whatever languages you want to run your analysis with its container based task graph. This week Daniel Whitenack shares the story of how the project got started, how it works under the covers, and how you can get started using it today!
Are you looking for a podcast that discusses the tools, techniques, and culture of data engineering? Then you’ve come to the right spot!