© 2021 Strange Loop
Let's face it: most people would never think of implementing data streams with Elasticsearch because this is not what Elasticsearch is known for. But what if I told you that the support for data streams in Elasticsearch is not only possible but also — awesome?
This talk will revisit Elasticsearch storage's architecture and explain why it is wise to handle data streams with it. It will show an entertaining demo that showcases how to store and compute data streams and transforming them into insight using only native features. Then it will explain how Elasticsearch addresses questions like — high-availability, scalability, constant-time latency, data volume, and how to retain years of data.
Ricardo is Principal Developer Advocate 🥑 at Elastic—the company behind the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash), where he does community advocacy for North America. With +20 years of experience, he may have learned a thing or two about Distributed Systems, Databases, Streaming Data, and Big Data. Before Elastic, he worked for other vendors such as Confluent, Oracle, Red Hat, and different consulting firms. These days Ricardo spends most of his time making developers fall in love with technology. While not working, he loves barbecuing in his backyard with his family and friends, where he gets the chance to talk about anything that is not IT-related. He lives in North Carolina, USA, with his wife and son. Follow Ricardo on Twitter: @riferrei