Data Engineering Podcast


This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

Support the show!

12 March 2018

Database Refactoring Patterns with Pramod Sadalage - Episode 22 - E22

Rewind 10 seconds
1X
Skip 30 seconds ahead
0:00/0:00

Share on social media:


Summary

As software lifecycles move faster, the database needs to be able to keep up. Practices such as version controlled migration scripts and iterative schema evolution provide the necessary mechanisms to ensure that your data layer is as agile as your application. Pramod Sadalage saw the need for these capabilities during the early days of the introduction of modern development practices and co-authored a book to codify a large number of patterns to aid practitioners, and in this episode he reflects on the current state of affairs and how things have changed over the past 12 years.

Preamble

  • Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure
  • When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at dataengineeringpodcast.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your data pipelines or trying out the tools you hear about on the show.
  • Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.
  • You can help support the show by checking out the Patreon page which is linked from the site.
  • To help other people find the show you can leave a review on iTunes, or Google Play Music, and tell your friends and co-workers
  • Your host is Tobias Macey and today I’m interviewing Pramod Sadalage about refactoring databases and integrating database design into an iterative development workflow

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • You first co-authored Refactoring Databases in 2006. What was the state of software and database system development at the time and why did you find it necessary to write a book on this subject?
  • What are the characteristics of a database that make them more difficult to manage in an iterative context?
  • How does the practice of refactoring in the context of a database compare to that of software?
  • How has the prevalence of data abstractions such as ORMs or ODMs impacted the practice of schema design and evolution?
  • Is there a difference in strategy when refactoring the data layer of a system when using a non-relational storage system?
  • How has the DevOps movement and the increased focus on automation affected the state of the art in database versioning and evolution?
  • What have you found to be the most problematic aspects of databases when trying to evolve the functionality of a system?
  • Looking back over the past 12 years, what has changed in the areas of database design and evolution?
    • How has the landscape of tooling for managing and applying database versioning changed since you first wrote Refactoring Databases?
    • What do you see as the biggest challenges facing us over the next few years?


Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast


Share on social media:


Listen in your favorite app:



More options

Here are shows you might like

See show recommendations
AI Engineering Podcast
Tobias Macey
The Python Podcast.__init__
Tobias Macey