EPISODE · Sep 29, 2021 · 1H 6M
55: Tables vs. Streams and Defining Real-Time with Pete Goddard of Deephaven Data Labs
from The Data Stack Show · host Rudderstack
Highlights from this week’s conversation include:Pete’s background in data engineering and capital market trading (2:10)Comparison of the tooling from 2012 when Deephaven started with that of today (10:30)Taking a closer look at defining real-time data (19:47)Getting non-technical people, clients, and developers all on the same platform (36:11)Deephaven’s incremental update model (40:25)Kafka, timely data flow, and Deephaven (44:22)Use cases for Deephaven (51:52)Going to GitHub to try out Deephaven (1:02:43)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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What this episode covers
On this week’s episode of The Data Stack Show, Eric and Kostas are joined by Pete Goddard, founding partner and CEO at Deephaven Data Labs. Deephaven’s query engine utilizes real-time data and creates a framework to make people productive with that engine.
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55: Tables vs. Streams and Defining Real-Time with Pete Goddard of Deephaven Data Labs
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