[ Ссылка ] | Welcome back for Episode 16 of Ask Confluent where we answer the questions you have about all things Confluent, Kafka, the Cloud, and specifically in this episode, ksqlDB! In today's episode Gwen Shapira is joined by Vinoth Chandar, who previously worked at Uber, is the creator of Apache Hudi and is one of the main drivers behind the ksqlDB project. Vinoth and Gwen spend a good bit of time discussing ksqlDB, what its function is, what are some of the usecases that come out of it and what types of applications can be built with it. From there, the two move into variety of questions including ones about ksqlDB itself, what's the best version of Apache Kafka right now and what the one main issue is with Confluent Cloud...you won't want to miss Episode 16!

1:11 explain what ksqlDB is
3:19 what kind of applications would i build with ksqlDB?
9:14 ksqlDB demo (on youtube)
9:30 Is ksqlDB just another consumer of Kafka? Or is it another deep abstraction of Kafka?
12:30 want more examples on git
13:09 What kind of vulnerabilities are there?
15:07 Any ksqlDB client available? client -center?
17:20 Need topology view of all sqls that we create
highly available is top priority!
20:57 On apache kafka 2.3 video -- thoughts on the latest apache kafka 2.3.1?
21:49 which version of apache kafka is best for performance improvements with without any breaking changes exisiting config and functionality?
25:45 compliments for ksqlDB!
23:56 "what is apache kafka?" video, problem with confluent cloud is max retention period is currently one month.



ABOUT CONFLUENT
Confluent, founded by the creators of Apache Kafka®, enables organizations to harness business value of live data. The Confluent Platform manages the barrage of stream data and makes it available throughout an organization. It provides various industries, from retail, logistics and manufacturing, to financial services and online social networking, a scalable, unified, real-time data pipeline that enables applications ranging from large volume data integration to big data analysis with Hadoop to real-time stream processing. To learn more, please visit [ Ссылка ]

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