The Emerging Blueprint for Agentic Apps

Providing your agent with live application state, historical data and a unified security model means stitching together infrastructure with pipelines you need to monitor and fix.

What if you could skip the data transfer altogether? Lake Transactional/Analytical Processing (LTAP) lets transactions and analytics read from the same copy of data by storing it in open formats on standard Postgres.

Join Reynold Xin, Databricks Co-founder and Chief Architect, on Nov 10-12 for an overview of this new architecture, a demo and benchmark. We’ll cover:

[li indent=0 align=left]How LTAP brings agent memory, application state and historical data under the same permissions[li indent=0 align=left]Removing sync intervals as a bottleneck for the agent memory loop while maintaining performance and availability[li indent=0 align=left]Compatibility with your drivers, extensions and ORMs by running on standard Postgres Registrants receive resources to further explore the presented materials after the event.

*Japanese and Korean captions available

[img width=543]//f3bb08b8efc611081e05f77b02395fcc.cdn.bubble.io/f1793662804029x232513514349971680/richtext_content.png