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Using Kafka and Pinot for User-Facing Real-Time Analytics
March 16 @ 6:00 pm - 8:00 pmFree
Apache Kafka is the de facto standard for real-time event streaming, but what do you do if you want to perform user-facing, ad-hoc, real-time analytics too? That’s a hard problem. Apache Pinot solves it, and the two together are like chocolate and peanut butter, peaches and cream, and Steve Rogers and Peggy Carter. Come to this talk for an introduction to both systems and a view of how they work together.
About Apache Pinot:
Pinot is a real-time distributed OLAP datastore, built to deliver scalable real-time analytics with low latency. It can ingest from batch data sources (such as Hadoop HDFS, Amazon S3, Azure ADLS, Google Cloud Storage) as well as stream data sources (such as Apache Kafka).
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Pinot was built by engineers at LinkedIn and Uber and is designed to scale up and out with no upper bound. Performance always remains constant based on the size of your cluster and an expected query per second (QPS) threshold.