Michael Drogalis (@MichaelDrogalis, Product Manager @Confluentinc) talks about the evolution of Kafka, the challenges of data management with event-driven systems, and the ksqlDB Database.

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SHOW NOTES:

• Confluent Homepage
• ksqlDB Homepage
• How Real-Time Stream Processing Works with ksqlDB
• How Real-Time Materialized Views Work with ksqlDB
• How Real-Time Stream Processing Safely Scales with ksqlDB

Topic 1 - Welcome to the show. Before we dive into this new database, let’s talk a little bit about your background. 

Topic 2 - Let’s first talk about Kafka. What is it,. what does it do, and what are common use-cases that use Kafka?

Topic 3 - Kafka handles all these streams of data / events, but there are a bunch of other pieces needed to connect the data to the applications. What are those pieces, and where are their often challenges?

Topic 4 - Let’s talk about this new project - ksqlDB. It’s real-time, it’s Kafka and it’s SQL. Walk us through how it was created and the types of challenges it solves for. 

Topic 5 - How is ksqlDB different from using other SQL databases? 

Topic 6 - What are some of the initial ways that you’re seeing ksqlDB being used? Is it beginning to allow new use-cases to emerge?

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