Using Apache Kafka and Pinot for User-Facing Real-Time Analytics

Learn how Apache Kafka and Pinot perform user-facing, ad-hoc, real-time analytics to millions of users at a time.

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About this Event

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 where Apache Pinot comes in.

Apache Pinot is a realtime distributed OLAP datastore, which is used to deliver scalable real time analytics with low latency. It can ingest data from batch data sources (S3, HDFS, Azure Data Lake, Google Cloud Storage) as well as streaming sources such as Kafka. Pinot is used extensively at LinkedIn and Uber to power many analytical applications such as Who Viewed My Profile, Ad Analytics, Talent Analytics, Uber Eats and many more serving 100k+ queries per second while ingesting 1Million+ events per second.

Apache Kafka's highly performant, distributed, fault-tolerant, real-time publish-subscribe messaging platform powers big data solutions at Airbnb, LinkedIn, MailChimp, Netflix, the New York Times, Oracle, PayPal, Pinterest, Spotify, Twitter, Uber, Wikimedia Foundation, and countless other businesses.

Come hear from Tim Berglund, Senior Director of Developer Advocacy at Confluent, and Neha Power, Founding Engineer at a stealth-mode startup, with an introduction to both systems and a view of how they work together.

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Please register via EventBrite:
https://www.eventbrite.com/e/using-apache-kafka-and-pinot-for-user-facing-real-time-analytics-live-tickets-132666554235

This event is in partnership with:
Galvenize www.galvanize.com/
Big Data and Analytics World Meetup https://www.meetup.com/Big-Data-and-Analytics-World/
and
Apache Pinot meetup https://www.meetup.com/apache-pinot/