Utilizing the true potential of data streaming is key to business success.
In this Data (R)evolution episode, we're joined by Josep Prat and Filip Yonov to dive into the transformative features of Apache Kafka and its evolving role in data architecture. They discuss the critical importance of collaboration and feedback in enhancing Kafka's capabilities, the future of "lake house" technology, exciting updates from the Open Source Program Office (OSPO), and the importance of Kafka's readiness to support evolving data formats—making it a backbone for modern data ecosystems.
Key Takeaways:
Resources:
Timestamps:
[05:49] Kafka servers have theoretical storage limits
[09:29] Test storage proposal process for Apache Kafka
[17:38] LinkedIn conducted an experiment merging Xcode versions
[22:11] Data lake evolving into lake house architectures
[25:00] Broker pushes data to remote storage, plugin handles retrieval and format translation
[26:40] Kafka excels at high-speed, high-volume data
[32:18] Kafka data consumption evolving with new options
[40:19] Managing metadata for conversion on community level
[47:45] Kafka's potential as a widely used API