Kafka Streams + H2O.ai + TensorFlow (Video Recording / Live Demo)

I do a lot of presentations these days at meetups and conferences about how to leverage Apache Kafka and Kafka Streams to apply analytic models (built with H2O, TensorFlow, DeepLearning4J and other frameworks) to scalable, mission-critical environments. As many attendees have asked me, I created a video recording about this talk (focusing on live demos).
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Why I Move (Back) to Open Source for Messaging, Integration and Stream Processing

After three great years at TIBCO Software, I move back to open source and join Confluent, the company behind the open source project Apache Kafka to build mission-critical, scalable infrastructures for messaging, integration and stream processsing. In this blog post, I want to share why I see the future for middleware and big data analytics in open source technologies, why I really like Confluent, what I will focus on in the next months, and why I am so excited about this next step in my career.
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Comparison of Stream Processing Frameworks and Products

See how stream processing / streaming analytics frameworks (e.g. Apache Spark, Apache Flink, Amazon Kinesis) and products (e.g. TIBCO StreamBase, Software AG’s Apama, IBM InfoSphere Streams) are categorized and compared. Besides, understand how stream processing is related to Big Data platforms such as Apache Hadoop and machine learning (e.g. R, SAS, MATLAB).
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TIBCO BusinessWorks and StreamBase for Big Data Integration and Streaming Analytics with Apache Hadoop and Impala

Apache Hadoop is getting more and more relevant. Not just for big data processing (e.g. MapReduce), but also in fast data processing (e.g. stream processing). Recently, I published two blog posts on the TIBCO blog to show how you can leverage TIBCO BusinessWorks 6 and TIBCO StreamBase to realize big data and fast data Hadoop use cases.
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