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Michael Drogalis

8 Podcast Episodes

Latest 9 Oct 2021 | Updated Daily

Weekly hand curated podcast episodes for learning

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Advanced Stream Processing with ksqlDB ft. Michael Drogalis

Streaming Audio: A Confluent podcast about Apache Kafka®

ksqlDB makes it easy to read, write, process, and transform data on Apache Kafka®, the de facto event streaming platform. With simple SQL syntax, pre-built connectors, and materialized views, ksqlDB’s powerful stream processing capabilities enable you to quickly start processing real-time data at scale. But how does ksqlDB work? In this episode, Michael Drogalis (Principal Product Manager, Product Management, Confluent) previews an all-new Confluent Developer course: Inside ksqlDB, where he provides a full overview of ksqlDB’s internal architecture and delves into advanced ksqlDB features. When it comes to ksqlDB or Kafka Streams, there’s one principle to keep in mind: ksqlDB and Kafka Streams share a runtime. ksqlDB runs its SQL queries by dynamically writing Kafka Streams typologies. Leveraging Confluent Cloud makes it even easier to use ksqlDB.Once you are familiar with ksqlDB’s basic design, you’ll be able to troubleshoot problems and build real-time applications more effectively. The Inside ksqlDB course is designed to help you advance in ksqlDB and Kafka. Paired with hands-on exercises and ready-to-use codes, the course covers topics including: ksqlDB architectureHow stateless and stateful operations workStreaming joins Table-table joinsElastic scaling High availabilityMichael also sheds light on ksqlDB’s roadmap: Building out the query layer so that is highly scalable, making it able to execute thousands of concurrent subscriptionsMaking Confluent Cloud the best place to run ksqlDB and process streamsTune in to this episode to find out more about the Inside ksqlDB course on Confluent Developer. The all-new website provides diverse and comprehensive resources for developers looking to learn about Kafka and Confluent. You’ll find free courses, tutorials, getting started guides, quick starts for 60+ event streaming patterns, and more—all in a single destination. EPISODE LINKSInside ksqlDB Course ksqlDB 101 CourseHow ksqlDB Works: Internal Architecture and Advanced FeaturesHow Real-Time Stream Processing Safely Scales with ksqlDB, AnimatedHow Real-Time Materialized Views Work with ksqlDB, AnimatedHow Real-Time Stream Processing Works with ksqlDB, AnimatedWatch the video version of this podcastJoin the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperLive demo: Intro to Event-Driven Microservices with ConfluentUse PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)

28mins

11 Aug 2021

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Drill to Detail Ep.90 'Apache Kafka, Real-Time Stream Processing and ksqlDB' with Special Guest Michael Drogalis

Drill to Detail

Mark Rittman is joined in this episode by Michale Drogalis, Product Manager at Confluent to talk about the history of Apache Kafka and real-time stream processing, the origins of kSQL and kSQLdb and the rationale and use-cases addressed by these products.ksqldDB product homepage Introducing ksqlDB Blog PostKafka Streams vs. ksqlDB Blog Post

39mins

20 May 2021

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kSQLDB: Kafka Streaming Interface with Michael Drogalis

Podcast – Software Engineering Daily

Kafka is a distributed stream processing system that is commonly used for storing large volumes of append-only event data. Kafka has been open source for almost a decade, and as the project has matured, it has been used for new kinds of applications.  Kafka’s pubsub interface for writing and reading topics is not ideal for all of these applications, which has led to the creation of ksqlDB, a database system built for streaming applications that uses Kafka as the underlying infrastructure for storing data. Michael Drogalis is a principal product manager at Confluent, where he helped develop ksqlDB. Michael joins the show to discuss ksqlDB, including the architecture, the query semantics, and the applications which might want a database that focuses on streams. We have done many great shows on Kafka in the past, which you can find on SoftwareDaily.com. Also, if you are interested in writing about Kafka, we have a new writing feature that you can check out by going to SoftwareDaily.com/write. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post kSQLDB: Kafka Streaming Interface with Michael Drogalis appeared first on Software Engineering Daily.

48mins

7 Apr 2020

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kSQLDB: Kafka Streaming Interface with Michael Drogalis

Data – Software Engineering Daily

Kafka is a distributed stream processing system that is commonly used for storing large volumes of append-only event data. Kafka has been open source for almost a decade, and as the project has matured, it has been used for new kinds of applications.  Kafka’s pubsub interface for writing and reading topics is not ideal for all of these applications, which has led to the creation of ksqlDB, a database system built for streaming applications that uses Kafka as the underlying infrastructure for storing data. Michael Drogalis is a principal product manager at Confluent, where he helped develop ksqlDB. Michael joins the show to discuss ksqlDB, including the architecture, the query semantics, and the applications which might want a database that focuses on streams. We have done many great shows on Kafka in the past, which you can find on SoftwareDaily.com. Also, if you are interested in writing about Kafka, we have a new writing feature that you can check out by going to SoftwareDaily.com/write. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post kSQLDB: Kafka Streaming Interface with Michael Drogalis appeared first on Software Engineering Daily.

42mins

7 Apr 2020

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kSQLDB: Kafka Streaming Interface with Michael Drogalis

Software Engineering Daily

Kafka is a distributed stream processing system that is commonly used for storing large volumes of append-only event data. Kafka has been open source for almost a decade, and as the project has matured, it has been used for new kinds of applications.  Kafka’s pubsub interface for writing and reading topics is not ideal for all of these applications, which has led to the creation of ksqlDB, a database system built for streaming applications that uses Kafka as the underlying infrastructure for storing data. Michael Drogalis is a principal product manager at Confluent, where he helped develop ksqlDB. Michael joins the show to discuss ksqlDB, including the architecture, the query semantics, and the applications which might want a database that focuses on streams. We have done many great shows on Kafka in the past, which you can find on SoftwareDaily.com. Also, if you are interested in writing about Kafka, we have a new writing feature that you can check out by going to SoftwareDaily.com/write. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post kSQLDB: Kafka Streaming Interface with Michael Drogalis appeared first on Software Engineering Daily.

48mins

7 Apr 2020

Episode artwork

kSQLDB: Kafka Streaming Interface with Michael Drogalis

Software Daily

Kafka is a distributed stream processing system that is commonly used for storing large volumes of append-only event data. Kafka has been open source for almost a decade, and as the project has matured, it has been used for new kinds of applications. Kafka’s pubsub interface for writing and reading topics is not ideal for all of these applications, which has led to the creation of ksqlDB, a database system built for streaming applications that uses Kafka as the underlying infrastructure for storing data.Michael Drogalis is a principal product manager at Confluent, where he helped develop ksqlDB. Michael joins the show to discuss ksqlDB, including the architecture, the query semantics, and the applications which might want a database that focuses on streams. We have done many great shows on Kafka in the past, which you can find on SoftwareDaily.com. Also, if you are interested in writing about Kafka, we have a new writing feature that you can check out by going to SoftwareDaily.com/write.

7 Apr 2020

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Why is Stream Processing Hard? ft. Michael Drogalis

Streaming Audio: A Confluent podcast about Apache Kafka®

Tim Berglund and Michael Drogalis (Product Lead for Kafka Streams and KSQL, Confluent) talk about all things stream processing: why it’s complex, how it's evolved, and what’s on the horizon to make it simpler.

45mins

29 May 2019

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1: Michael Drogalis on Pyrostore's Acquisition, the future of Onyx, and stream processing

The REPL

Michael Drogalis discusses Pyroclasts's recent acquisition by Confluent, high performance stream processing, working on large Clojure programs, and some of Onyx's technical innovations. Welcoming The Distributed Masonry Team to Confluent Pyrostore Announcing Pyrostore’s tiered storage Component Aeron Mechanical Sympathy Mailing List Michael Drogalis on Twitter

30mins

29 Aug 2018