Inside Google’s Database Infrastructure for the AI Era

Inside Google’s Database Infrastructure for the AI Era

Author: Software Engineering Daily September 15, 2026 Duration: 1:18:26

Historically, databases were responsible for storing data and returning exact results in response to queries. However, AI is now bending that contract in a new direction. Applications increasingly expect structured and unstructured data to come together. This is pushing databases into territory that looks more like search, where relevance and ranking matter and results are no longer strictly exact. Agents are also beginning to write their own queries and even propose their own schemas, which raises new questions about how data should be structured, governed, and trusted.

Sailesh Krishnamurthy is a VP of Engineering at Google, and in this episode he joins Matt Merrill to discuss his background, how databases have evolved over the past fifty years, and where the field is heading as AI reshapes how data is queried, structured, and trusted.

Sponsorship inquiries:
sponsor@softwareengineeringdaily.com

The post Inside Google’s Database Infrastructure for the AI Era appeared first on Software Engineering Daily.


Dive deep into the conversations shaping the future of artificial intelligence with the Machine Learning Archives-Software Engineering Daily. This curated collection pulls from the broader Software Engineering Daily library, focusing entirely on the intricate world of ML engineering. Each episode features a detailed, technical interview with engineers, researchers, and architects who are building the systems behind today's most advanced AI. You'll hear them break down complex topics like model deployment, data pipeline challenges, and the practical trade-offs involved in taking research from a notebook into production. The discussions are grounded in real-world implementation, moving beyond theoretical concepts to explore the tools, failures, and successes that define the field. For developers and technical leaders looking to understand the nuts and bolts of applied machine learning, this podcast offers a valuable archive of knowledge. It's a direct line to the practitioners who are solving hard problems every day, providing insights you can apply to your own work. Tune in to gain a clearer perspective on how machine learning is integrated into modern software, one detailed conversation at a time.
Author: Language: en-us Episodes: 50

Software Engineering Daily
Podcast Episodes
Autonomous Drone Delivery at Scale [not-audio_url] [/not-audio_url]

Duration: 50:30
Autonomous drone delivery has long been the stuff of science fiction, but ongoing advances have moved the space from experimental to operational. Zipline is one of the leading companies in this space, with drones that ch…
The European Startup Scene [not-audio_url] [/not-audio_url]

Duration: 48:57
Europe’s startup ecosystem is maturing rapidly, with companies like Revolut, Lovable, and Legora demonstrating that world-class technology businesses can be built and scaled on the continent. While the US remains the dom…
React Native at Scale [not-audio_url] [/not-audio_url]

Duration: 45:35
React Native is an open source framework developed by Meta that allows engineers to build mobile applications for both iOS and Android using a single JavaScript codebase. The framework bridges the gap between web develop…
Formal Methods as Agent Guardrails [not-audio_url] [/not-audio_url]

Duration: 48:32
Formal methods are a branch of mathematics and computer science focused on proving the correctness of systems, and they have long promised a more rigorous foundation for software. However, their complexity has kept them…
Open Source Sustainability [not-audio_url] [/not-audio_url]

Duration: 58:43
Open source software underpins nearly every modern application, including frameworks powering the most popular websites, to the libraries securing financial backend systems. However, while open source drives collaboratio…
Vespa AI and Surpassing the Limits of Vector Search [not-audio_url] [/not-audio_url]

Duration: 38:35
Vector search has risen to become a foundational tool in modern search and retrieval systems, including the RAG pipelines that power many AI applications. However, the demands on retrieval systems are growing more sophis…
SmartBear and Multi-Agent QA [not-audio_url] [/not-audio_url]

Duration: 55:15
AI coding tools have dramatically accelerated the pace of development, and the bottleneck in the software development lifecycle has shifted to code validation and testing. However, the conventional tools and workflows th…
The Ethics of Autonomous Weapons Systems [not-audio_url] [/not-audio_url]

Duration: 1:06:40
Artificial intelligence is transforming warfare faster than the legal and ethical frameworks designed to govern it. Militaries around the world are deploying AI-powered decision support systems to identify targets, asses…
Open-Weight AI Models [not-audio_url] [/not-audio_url]

Duration: 50:14
Open-weight models are AI systems whose trained parameters are publicly released, which allows developers to run, fine-tune, and deploy them independently rather than accessing them only through a hosted API. While close…