THURSDAY, SEPTEMBER 22, 2016 |
11:00am PT / 2:00pm ET |
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The goal of a real-time big data architecture is to harness the power of data in motion, accelerating time-to-insight and time-to-action, and that requires a high-performance data pipeline – infrastructure to route data from multiple sources to multiple destinations, often at high throughput, and always with low latency. In this webinar, we'll describe how to build a high-performance data pipeline using distributed messaging, stream processing, and a NoSQL database – as well as reference architectures for real-time big data and real-world use cases. Confluent Platform, a scalable stream data platform based on Apache Kafka, is a distributed messaging system with a built-in framework for stream processing – it's the plumbing. Couchbase Server, a NoSQL database with a SQL-based query language, is a distributed database with a streaming replication protocol – it's the faucet, and the sink. In this webinar, you'll learn how to:
- Build data pipelines for real-time big data
- Utilize distributed messaging with Apache Kafka
- Perform stream processing with Kafka Streams
- Utilize a NoSQL database with Couchbase Server
- Integrate Couchbase Server with Confluent Platform
Register today to learn about Real-time Big Data. Audio is streamed over the Internet, so turn up your computer speakers! |
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PRESENTERS |
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David Tucker Director of Partner Engineering Confluent |
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Shane K Johnson Senior Manager of Product Marketing Couchbase |
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MODERATOR |
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Stephen Faig Business Development Manager Unisphere Research and DBTA |
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