Apache Kafka® 101: ksqlDB



https://cnfl.io/kafka-101-module-12 | ksqlDB is an event streaming database optimized for building stream processing applications in which queries are defined in SQL. It performs continuous processing of event streams and exposes the results to applications like a database. Watch Tim Berglund (Senior Director of Developer Experience, Confluent) show you an example of ksqlDB in action.

Use the promo code KAFKA101 to get $101 of free Confluent Cloud usage: https://www.confluent.io/confluent-cloud/tryfree/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka

Promo code details: https://www.confluent.io/confluent-cloud-promo-disclaimer/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka

LEARN MORE
► ksqlDB 101: https://developer.confluent.io/learn-kafka/ksqldb/intro/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► Inside ksqlDB: https://developer.confluent.io//learn-kafka/inside-ksqldb/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► ksqlDB: https://docs.confluent.io/platform/current/ksqldb/index.html?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► ksqlDB Examples: https://ksqldb.io/examples.html?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► Building Data Pipelines with Apache Kafka® and Confluent: https://developer.confluent.io/learn-kafka/data-pipelines/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► Apache Kafka Fundamentals: The Concept of Streams and Tables ft. Michael Noll: https://developer.confluent.io/podcast/apache-kafka-fundamentals-the-concept-of-streams-and-tables-ft-michael-noll?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► How Real-Time Stream Processing Safely Scales with ksqlDB, Animated: https://www.confluent.io/blog/how-real-time-stream-processing-safely-scales-with-ksqldb/?utm_source=youtube&utm_medium=video&utm_campaign=tm.devx_ch.cd-apache-kafka-101_content.apache-kafka
► Kafka Summit: Apache Kafka and ksqlDB in Action – Let’s Build a Streaming Data Pipeline: https://rmoff.dev/build-a-streaming-data-pipeline

CONNECT
Subscribe: https://youtube.com/c/confluent?sub_confirmation=1
Site: https://confluent.io
GitHub: https://github.com/confluentinc
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LinkedIn: https://www.linkedin.com/company/confluent
Instagram: https://www.instagram.com/confluent_inc

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 https://confluent.io

#kafka #kafkastreams #streamprocessing #apachekafka #confluent

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8 thoughts on “Apache Kafka® 101: ksqlDB”
  1. Nice introduction & nice music … BTW any provide the link of the complete music ?

  2. 00:38 I swear the more I watch Tim the more he looks, sounds and acts like Dr.Cox from Scrubs. Nicer Less angry version but the sarcasm is on point. Much respect. Great series. Learning a lot from them.

  3. Hi Tim, Do you have a book written on Kafka? or are you writing one? if yes, please let me know where I can or will be able to buy it. Please do put in the examples that you've shown in devox.

  4. What is the underlying engine for these materialized views index storage ? Is it RockDB or something? How performant is it when it comes to large amounts of data like a million rows?

  5. 3:45 "The key would be a composite of movie title and release because they're in the Group By". Eh? Only "title" is in the Group By. Where is "release"?

  6. in the average rating example, is that SQL script still going to find the average rating even if Kafka cluster had a data retention policy set to, say, 7 days?!

  7. Thank you! Could you explain or recomment to read how fault tolerant does work in KsqlDB? Also how ksql has proven itself in production?

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