The Enterprise AI Show

The Enterprise AI Show explores the AI journey for Enterprise companies around the world. [formerly The Cloudcast]

As the AI revolution moves from experimentation to execution, The Enterprise AI Show provides the clarity needed to lead. Join Aaron Delp and Brian Gracely as they explore the intersection of generative AI, enterprise systems, and global business strategy. Each episode features clear-headed conversations with the people making actual decisions—founders, investors, and practitioners—focusing on the technical architectures and business models that drive real-world ROI.

New shows every Wednesday and Sunday.

Topics: Enterprise AI strategy · The AI Economy · LLMs in production · AI leadership · Agentic AI · Digital Sovereignty · Machine Learning · AI startups · Cloud Computing

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The Enterprise AI Show

The Cloudcast #342 - Understanding Databases in AWS

April 12, 2018 • Aaron Delp & Brian Gracely

0:00 | 31:00

Brian talks with Steve Abraham (Principal Solutions Architect @ Amazon Web Services) building and migrating databases in the cloud, how companies are managing migrations, the demands for open source databases, and how the worlds of database and serverless are intersecting.

Show Links:

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Show Notes

Topic 1 - Welcome to the show. Tell us a little bit about your background and also the areas you focus on at AWS.
Topic 2 - Let’s start by talking about the difference between new and existing databases. Does AWS see more demand for DB-migrations or new DBs in the cloud?
Topic 3 - What are some of the tools or services to migrate existing databases to AWS databases
Topic 4 - You’ve been a DBA in the past. How have you seen DBAs adapt to work on DBs in the cloud?
Topic 5 - What are some of the ways that AWS is improving or eliminating some of the need for constant DBA interactions and tuning, or "improving" the DBA experience? “Serverless databases”?
Topic 6 - Any tips for how companies address databases in a microservices world? Can you break up a monolithic database?
Topic 7 - How does AWS think about wiring together data-sources (databases, storage, etc.) with some of the advanced AI/ML services?

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