A Data Streaming Platform (DSP) is composed of six major inter-related components, covered in detail in this video. Each component has evolved over time to servce specific needs in the data streaming platform, but together form a whole that is greater than its sum.
While you can build your own DSP by following the outline in this video, you can also get started immediately with Confluent’s DSP today: https://cnfl.io/4dI8qWa
A DSP provides a complete solution for unified end-to-end data streaming. It provides all the necessary capabilities to succeed in data streaming, incuding data connectivity, integration, discovery, security, and management. Ultimately, a DSP makes it easy for you to build, use, and share data all across your organization for any use case.
RELATED RESOURCES
► What Is a Data Streaming Platform (DSP)? - https://cnfl.io/4jm5oup
► Data best practices and CDC - https://cnfl.io/3X4BLo6
► Kafka Connect 101 - https://cnfl.io/4fOdNFc
► How to address bad data in your event streams - https://medium.com/confluent/preventing-and-fixing-bad-data-in-event-streams-part-1-27bf2a99b48e
CHAPTERS
00:00 - Introduction, a DSP’s Six Parts
00:30 - Pyramid Model of Data Streaming Evolution
00:46 - Apache Kafka (Part 1)
1:55 - Schema Registry (Part 2)
3:53 - Data Portal (Part 3)
5:44 - Connectors (Part 4)
7:30 - Stream Processor Flink (Part 5)
8:40 - Tableflow (Part 6)
10:33 - Conclusion
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ABOUT CONFLUENT
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.
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