Shownotes Transcript
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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**CLOUD NEWS OF THE WEEK **- http://bit.ly/cloudcast-cnotw)**CHECK OUT OUR NEW PODCAST - ****"CLOUDCAST BASICS"**)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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