Summary
Data has permeated every aspect of our lives and the products that we interact with. As a result, end users and customers have come to expect interactions and updates with services and analytics to be fast and up to date. In this episode Shruti Bhat gives her view on the state of the ecosystem for real-time data and the work that she and her team at Rockset is doing to make it easier for engineers to build those experiences.
Announcements
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IntroductionHow did you get involved in the area of data management?Can you describe what is driving the adoption of real-time analytics?architectural patterns for real-time analyticssources of latency in the path from data creation to end-userend-user/customer expectations for time to insightdiffering expectations between internal and external consumersscales of data that are reasonable for real-time vs. batchWhat are the most interesting, innovative, or unexpected ways that you have seen real-time architectures implemented?What are the most interesting, unexpected, or challenging lessons that you have learned while working on Rockset?When is Rockset the wrong choice?What do you have planned for the future of Rockset?Contact Info
LinkedIn@shrutibhat on TwitterParting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?Links
RocksetPodcast EpisodeEmbedded AnalyticsConfluentKafkaAWS KinesisLambda ArchitectureData ObservabilityData MeshDynamoDB StreamsMongoDB Change StreamsBigeyeMonte Carlo DataThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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