Use CCLOUD50 to get an additional $50 of free Confluent Cloud- (details)

Streaming Audio Podcast

Listen to Tim Berglund, Gwen Shapira, and guests unpack a variety of topics surrounding Apache Kafka®, Confluent, real-time data streaming, and the cloud.

Integration
  • All Topics
  • Apache Kafka
  • Architecture
  • Ask Confluent
  • Big Ideas
  • Clients
  • Cloud
  • Confluent Platform
  • Distributed Systems Engineering
  • Event Streaming
  • Integration
  • Kafka
  • Kafka 101
  • Kafka Connect
  • Kafka Streams
  • ksqlDB
  • Kubernetes
  • Microservices
  • Schema Registry
  • Spring
  • Stream Processing
  • Streaming Audio Special
  • Use Cases
Subscribe
Episode 75December 23, 2019 | 50 min

Apache Kafka and Apache Druid – The Perfect Pair ft. Rachel Pedreschi

Rachel Pedreschi's involvement in the open source community focuses primarily on Apache Druid, a real-time, high-performance datastore that provides fast, sub-second analytics and complements another powerful open source project as well: Apache Kafka®. Together, Kafka and Druid provide real-time event streaming and high-performance streaming analytics with powerful visualizations.

Episode 63October 28, 2019 | 43 min

Data Integration with Apache Kafka and Attunity

From change data capture (CDC) to business development, connecting Apache Kafka® environments, and customer success stories, Graham Hainbach discusses the possibilities of data integration with Kafka and Attunity using Replicate, Compose, and Manager. He also shares real-life examples of how Attunity best leverages Kafka in their systems.

Episode 58October 2, 2019 | 43 min

MySQL, Cassandra, BigQuery, and Streaming Analytics with Joy Gao

Joy Gao chats with Tim Berglund about all things related to streaming ETL—how it works, its benefits, and the implementation and operational challenges involved. She describes the streaming ETL architecture at WePay from MySQL/Cassandra to BigQuery using Apache Kafka®, Kafka Connect, and Debezium.

Episode 52September 9, 2019 | 54 min

Connecting to Apache Kafka with Neo4j

Michael Hunger and David Allen discuss Neo4j basics and major features introduced in Neo4j 3.4.15. They'll cover the history of the integration and features in relation to Apache Kafka®, change data capture (CDC), using Neo4j to put graph operations into an event streaming application, and how GraphQL fits in with event streaming and GRANDstack.

Episode 41July 10, 2019 | 49 min

Change Data Capture with Debezium ft. Gunnar Morling

Gunnar Morling shares a little bit about what Debezium is, how it works, and which databases it supports. In addition to covering the various use cases and benefits from change data capture in the context of microservices, Gunnar walks us through the advantages of log-based CDC as implemented through Debezium over polling-based approaches, why you’d want to avoid dual writes to multiple resources, and working collaboratively with the community on Debezium.

Meet your hosts

Tim Berglund

Tim Berglund is a teacher, author, and technology leader with Confluent, where he serves as the senior director of developer advocacy. He can frequently be found at speaking at conferences in the U.S. and all over the world. Tim is the co-presenter of various O'Reilly training videos on topics ranging from Git to distributed systems, and he is the author of "Gradle Beyond the Basics." He lives in Littleton, CO, U.S., with the wife of his youth.

Gwen Shapira

Gwen Shapira is an engineering leader at Confluent. She has over 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. Gwen is the author of "Kafka: The Definitive Guide" and "Hadoop Application Architectures." Gwen is a frequent presenter at industry conferences, a PMC member on the Apache Kafka project, and a committer on Apache Sqoop™. When Gwen isn't building data pipelines or thinking up new features, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.

Got questions?

If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.

Email Us

Never miss an episode!

Be the first to get updates and new content

We will only share developer content and updates, including notifications when new content is added. We will never send you sales emails. 🙂 By subscribing, you understand we will process your personal information in accordance with our Privacy Statement.