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Streaming Data and Message-oriented Middleware Fundamentals

Video Description

This video series provides an overview to the world of streaming data and message-oriented middleware. There are three clips in this series:

  • Streaming Solutions for a Modern Enterprise Data Fabric. This first clip in the video series introduces data streaming, message-oriented middleware, and message queuing technology. We cover the complexities introduced by having multiple source systems send a torrent of information that need to be timestamped, dispatched, and sometimes duplicated. Learn why Extract, Transport, and Load (ETL) is no longer sufficient for most applications. Explore the modern realities of data integration including the new types of data sources that exist and the frequent requirements for real-time data. Learn why real-time data requires special attention, as it is the foundation for emergent technologies such as artificial intelligence.
  • Performance and Scalability in Streaming. This second clip in the video series covers the major factors that impact performance and scalability including throughput, storage, latency, and operations. Learn about the necessary architecture for streaming performance and scaling. Apache Kafka and RabbitMQ are introduced.
  • Major Players in Data Streaming. This third clip in the video series covers other vendors in the data streaming space including Amazon Kinesis, Apache Pulsar, and Streamlio. A roadmap is provided to migrate ETL to stream processing.