Organizations require systems and mechanisms in place to gather and analyze large amounts of data as it is created, in order to get insights and respond in real time for a wide range of usecases – real-time bidding, tracking and reporting impressions in ad-tech services, analyzing player actions, and establishing leaderboards in online gaming services, live tracking of flights, buses and cabs in mobility and logistics services, click-stream analysis in eCommerce and more. Stream processing data technologies enable them ingest data as it is created, process it, and analyze it as soon as it is accessible. In this video, we discuss the architectural patterns that you can use for streaming time-series data from Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters to Amazon Timestream for LiveAnalytics, followed by a demonstration of building an end-to-end pipeline using the Timestream Sink Connector that we open-sourced.
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