Using Apache Pulsar functions for data workflows at Narvar
Who is this presentation for?Data engineers, data architects, developers
Narvar is an intelligent customer experience platform that helps 650+ of the world’s most admired brands ensure that every touchpoint along the purchase journey engages consumers and enables emotional connections. With prepurchase delivery prediction, branded package tracking, seamless returns and exchanges, in-store experiences, and beyond, Narvar simplifies the everyday lives of consumers.
Karthik Ramasamy and Anand Madhavan walk you through how Narvar moved away from using a slew of technologies and consolidating their use cases using Apache Pulsar.
Narvar originally used a large collection of point technologies such as AWS Kinesis, Lambda, and Apache Kafka to satisfy its requirements for pub/sub messaging, message queuing, logging, and processing. After evaluating various technology options to help simplify and consolidate their data processing, Narvar selected Apache Pulsar due to its unified messaging and queuing model, ability to process data using lightweight functions, and guaranteed data durability.
- A basic understanding of data processing and messaging systems
What you'll learn
- Discover how retail use cases are elegantly mapped into Apache Pulsar and the production experiences
Karthik Ramasamy is the cofounder of Streamlio, a company building next-generation real-time processing engines. Karthik has more than two decades of experience working in parallel databases, big data infrastructure, and networking. Previously, he was engineering manager and technical lead for real-time analytics at Twitter, where he was the cocreator of Heron; cofounded Locomatix, a company that specialized in real-time stream processing on Hadoop and Cassandra using SQL (acquired by Twitter); worked briefly on parallel query scheduling at Greenplum (acquired by EMC for more than $300M); and designed and delivered platforms, protocols, databases, and high-availability solutions for network routers at Juniper. He’s the author of several patents, publications, and one best-selling book, Network Routing: Algorithms, Protocols, and Architectures. Karthik holds a PhD in computer science from the University of Wisconsin–Madison with a focus on databases, where he worked extensively in parallel database systems, query processing, scale-out technologies, storage engines, and online analytical systems. Several of these research projects were spun out as a company later acquired by Teradata.
Anand Madhavan is the vice president of engineering at Narvar. Previously, he was head of engineering for the Discover product at Snapchat and director of engineering at Twitter, where we worked on building out the ad serving system for Twitter Ads. He earned an MS in computer science from Stanford University.
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