When Data is Your Brand and Your Job with Joe Karlsson
Joe Karlsson, Data Engineer at Tinybird, joins Corey on Screaming in the Cloud to discuss what it’s like working in the world of data right now and how he manages the overlap between his social media presence and career. Corey and Joe chat about the rise of AI and whether or not we’re truly seeing advancements in that realm or just trendy marketing plays, and Joe shares why he feels data is getting a lot more attention these days and what it’s like to work in data at this time. Joe also shares insights into how his mental health has been impacted by having a career and social media presence that overlaps, and what steps he’s taken to mitigate the negative impact.
About Joe
Joe Karlsson (He/They) is a Software Engineer turned Developer Advocate at Tinybird. He empowers developers to think creatively when building data intensive applications through demos, blogs, videos, or whatever else developers need.
Joe's career has taken him from building out database best practices and demos for MongoDB, architecting and building one of the largest eCommerce websites in North America at Best Buy, and teaching at one of the most highly-rated software development boot camps on Earth. Joe is also a TEDx Speaker, film buff, and avid TikToker and Tweeter.
Links Referenced:
Tinybird: https://www.tinybird.co/
Personal website: https://joekarlsson.com
Tinybird: https://www.tinybird.co/
Personal website: https://joekarlsson.com
S19:E6 - How to make learning databases fun and approachable ( Joe Karlsson)
In this episode, we talk about making databases fun and approachable with Joe Karlsson, Senior Developer Advocate at Single Store DB. Joe talks about going from hating coding to loving it, the relationship between databases and backend work, and how people can bring creativity and fun into their learning and their work in databases.
Show Links
Partner with Dev & CodeNewbie! (sponsor)
SingleStore
Node.js
JavaScript
Python
SQL
Joe Karlsson
Joe's career has taken him from building out database best practices and demos for MongoDB, architecting and building one largest eCommerce websites in North America at Best Buy, and teaching at one of the most highly-rated software development boot camps on Earth. Joe is also a TEDx Speaker, film buff, and avid TikToker and Tweeter.
Making Analytical APIs Fast With Tinybird
Summary
Building an API for real-time data is a challenging project. Making it robust, scalable, and fast is a full time job. The team at Tinybird wants to make it easy to turn a continuous stream of data into a production ready API or data product. In this episode CEO Jorge Sancha explains how they have architected their system to handle high data throughput and fast response times, and why they have invested heavily in Clickhouse as the core of their platform. This is a great conversation about the challenges of building a maintainable business from a technical and product perspective.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management
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Your host is Tobias Macey and today I’m interviewing Jorge Sancha about Tinybird, a platform to easily build analytical APIs for real-time data
Interview
Introduction
How did you get involved in the area of data management?
Can you start by describing what you are building at Tinybird and the story behind it?
What are some of the types of use cases that your customers are focused on?
What are the areas of complexity that come up when building analytical APIs that are often overlooked when first designing a system to operate on and expose real-time data?
What are the supporting systems that are necessary and useful for operating this kind of system which contribute to the overall time and engineering cost beyond the baseline functionality?
How is the Tinybird platform architected?
How have the goals and implementation of Tinybird changed or evolved since you first began building it?
What was your criteria for selecting the core building block of your platform, and how did that lead to your choice to build on top of Clickhouse?
What are some of the sharp edges that you have run into while operating Clickhouse?
What are some of the custom tools or systems that you have built to help deal with them?
What are some of the performance challenges that an API built with Tinybird might run into?
What are the considerations that users should be aware of to avoid introducing performance issues?
How do you handle multi-tenancy in your platform? (e.g. separate clusters, in-database quotas, etc.)
For users of Tinybird, can you talk through the workflow of getting it integrated into their platform and designing an API from their data?
What are some of the most interesting, innovative, or unexpected ways that you have seen Tinybird used?
What are the most interesting, unexpected, or challenging lessons that you have learned while building and growing Tinybird?
When is Tinybird the wrong choice?
What do you have planned for the future of the product and business?
Contact Info
@jorgesancha on Twitter
LinkedIn
jorgesancha on GitHub
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
Tinybird
Carto
PostgreSQL
Podcast Episode
PostGIS
Clickhouse
Podcast Episode
Kafka
Tornado
Podcast.__init__ Episode
Redis
Formula 1
Web Application Firewall
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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