As a developer, it's crucial to understand the various types of databases available so you can choose the right tool for the job. In this episode, we're shining a spotlight on bitemporal databases with James Henderson, lead developer of of a new bitemporal database called XTDB.

You may have already created an ad-hoc bitemporal database without realizing it, but James and his team have been hard at work building a custom database that's tailor-made for situations where having two notions of time are essential. Join us to learn about the what and why of bitemporality and explore the process of designing and building a database in Clojure.

Ready to get started with XTDB? Visit https://www.xtdb.com/v2 to learn more.
Want to get involved with the XTDB community? Head over to https://discuss.xtdb.com.
Follow XTDB on Twitter at https://twitter.com/xtdb_com
 and Kris Jenkins at https://twitter.com/krisajenkins.
Connect with Kris on LinkedIn at https://www.linkedin.com/in/krisjenkins/.

Every business deals in data, but the internet age has ushered in an explosion of the number of different data formats we have to process from a number of different databases to get the job done. Ask any Data Scientist, and they’ll tell you a huge part of their job isn’t data science - it’s data engineering. Acquiring, processing and shipping data, and above all, understanding it. We’ve always had that task in the IT world, but these days it’s a whole discipline.

Today’s podcast sits down with the author of “The Fundamentals Of Data Engineering” to survey the landscape. To understand what data engineering is, and go deep into what a data engineer needs to understand to succeed.

In this episode we're exploring the Kotlin programming language with an expert from Google. What does Kotlin have to offer? Is it just a Java alternative, or has it turned into something much more ambitious? Along the way we manage to discuss Scala, Function Programming vs. Object Orientation, Editors, Higher Kinded Types, Elm, React, UI architectures and multiplatform programming. A very full episode!

Happy Path Programming - Haskell is not as scary as you think: https://pod.link/1531666706/episode/710a605d605fda251f2e83b8858615b8
The Kotlin Programming Language: https://kotlinlang.org/
Android Studio: https://developer.android.com/studio
Kris on Twitter: https://twitter.com/krisajenkins
Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

AI is the new hotness, but with new approaches come new problems of scale. How do you make raw data accessible to teams of data scientists and model-builders? How do build a repeatable deployment pipeline? And how do you monitor your models once they're in production? Today's episode goes through all these reality checks with author and expert Adi Polak, who's just released a new book on the subject.

Scaling Machine Learning With Spark (book): https://www.oreilly.com/library/view/scaling-machine-learning/9781098106812/
Kris on Twitter: https://twitter.com/krisajenkins
Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

Louis Pilfold joins us to talk about Gleam, a new language that runs on Erlang's BEAM. In creating Gleam, Louis has tried to bring a new level of developer-friendliness to Erlang's famously fault-tolerant platform.

If you're interested in building reliable distributed systems, exploring functional programming, learning new languages or finding out what it takes to design your own language, Louis is here to talk us through it all.

The Gleam language: https://gleam.run/
Gleam’s package repo: https://packages.gleam.run/
Gleam on Twitter: https://twitter.com/gleamlang
Kris on Twitter: https://twitter.com/krisajenkins
Kris on LinkedIn: https://www.linkedin.com/in/krisjenkins/