Adopting Real-Time Data At Organizations Of Every Size

Summary The term "real-time data" brings with it a combination of excitement, uncertainty, and skepticism. The promise of insights that are always accurate and up to date is appealing to organizations, but the technical realities to make it possible have been complex and expensive. In this episode Arjun Narayan explains how the technical barriers to adopting real-time data in your analytics and applications have become surmountable by organizations of all sizes. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. 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Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their extensive library of integrations enable you to automatically send data to hundreds of downstream tools. Sign up free at dataengineeringpodcast.com/rudder Build Data Pipelines. Not DAGs. That’s the spirit behind Upsolver SQLake, a new self-service data pipeline platform that lets you build batch and streaming pipelines without falling into the black hole of DAG-based orchestration. 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Your host is Tobias Macey and today I’m interviewing Arjun Narayan about the benefits of real-time data for teams of all sizes Interview Introduction How did you get involved in the area of data management? Can you describe what your conception of real-time data is and the benefits that it can provide? types of organizations/teams who are adopting real-time consumers of real-time data locations in data/application stacks where real-time needs to be integrated challenges (technical/infrastructure/talent) involved in adopting/supporting streaming/real-time lessons learned working with early customers that influenced design/implementation of Materialize to simplify adoption of real-time types of queries that are run on materialize vs. warehouse how real-time changes the way stakeholders think about the data sourcing real-time data What are the most interesting, innovative, or unexpected ways that you have seen real-time data used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Materialize to support real-time data applications? When is real-time the wrong choice? What do you have planned for the future of Materialize and real-time data? Contact Info @narayanarjun on Twitter Email LinkedIn Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers Links Materialize Podcast Episode Cockroach Labs Podcast Episode SQL Kafka Debezium Podcast Episode Change Data Capture Reverse ETL Pulsar Podcast Episode The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast