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More: https://current.confluent.io | Event stream infrastructure has become an important part of modern data stack in many organizations enabling them to rapidly ingest and process streaming data to gain real-time insight and take actions accordingly. Streaming storage systems such as Apache Kafka provide a storage layer to ingest and make data streams available in real-time. Streaming analytics(stream processing) systems and streaming databases are two platforms enabling users to gain real-time insight from their data streams. However, each of these systems is suitable for different use cases and one system alone may not be the right choice for all of your stream processing needs. In this talk we introduce both streaming analytics(also known as stream processing) and streaming databases and provide an overview of capabilities in each system. We also explore different categories of use cases and discuss which system is more appropriate for these use cases. Attendees will learn about streaming analytics and streaming database systems and their capabilities. This will enable them to choose the right platform for the real-time applications they built on top of streaming storage systems such as Apache Kafka. LEARN MORE ► Confluent Developer: https://developer.confluent.io CONNECT Subscribe on YouTube: / @confluentdeveloper Community Slack: confluentcommunity.slack.com X: https://x.com/confluentinc Linkedin: / confluent GitHub: https://github.com/confluentinc Site: https://developer.confluent.io ABOUT CONFLUENT DEVELOPER Confluent Developer provides comprehensive resources for developers looking to learn about Apache Kafka®, Apache Flink®, Confluent Cloud, Confluent Platform, and any other technology related to the broader Data Streaming Platform. Content on Confluent Developer includes courses, getting started guides, topical deep-dives, patterns, tutorials, and listings of community events. Learn more at https://developer.confluent.io. #apachekafka #apacheflink #confluent