---
title: "Building for the AI Era: Lakebase, Streaming, and Lakehouse Innovations  at VLDB 2026"
description: "Databricks previews its VLDB 2026 keynote, four accepted papers, a demo, and a sponsor talk covering database architecture, streaming, and Lakehouse optimization. Reynold Xin will introduce Lakebase, which separates serverless PostgreSQL compute from storage, and LTAP, a transactional-analytical model intended for AI-agent workloads; Lakebase stores data and write-ahead logs in cloud object storage and supports sub-second cold starts and copy-on-write branching. The papers describe a decade of Spark Structured Streaming evolution, including microbatch pipelining that improved throughput by up to 3x, stateful APIs, and fine-grained access control, alongside AutoLiquid’s CLUSTER BY AUTO and Ultron’s history-based query optimization. AutoLiquid outperformed customer-selected clustering keys on over 95% of evaluated workloads, while Ultron improved median join latency by 25% in production workloads. The program also includes an Enzyme demonstration of incremental materialized-view maintenance and a sponsor presentation on LakehouseRT and the Reyden engine."
---

# Building for the AI Era: Lakebase, Streaming, and Lakehouse Innovations  at VLDB 2026

[Databricks](https://yomu.fyi/company/databricks) · Indrajit Roy, Ippokratis Pandis · Aug 27, 2026

**Type:** Announcement

## Summary

Databricks previews its VLDB 2026 keynote, four accepted papers, a demo, and a sponsor talk covering database architecture, streaming, and Lakehouse optimization. Reynold Xin will introduce Lakebase, which separates serverless PostgreSQL compute from storage, and LTAP, a transactional-analytical model intended for AI-agent workloads; Lakebase stores data and write-ahead logs in cloud object storage and supports sub-second cold starts and copy-on-write branching. The papers describe a decade of Spark Structured Streaming evolution, including microbatch pipelining that improved throughput by up to 3x, stateful APIs, and fine-grained access control, alongside AutoLiquid’s CLUSTER BY AUTO and Ultron’s history-based query optimization. AutoLiquid outperformed customer-selected clustering keys on over 95% of evaluated workloads, while Ultron improved median join latency by 25% in production workloads. The program also includes an Enzyme demonstration of incremental materialized-view maintenance and a sponsor presentation on LakehouseRT and the Reyden engine.

## Context

AI agent workloads are creating usage patterns involving millions of short-lived, deeply branched databases. The post states that traditional monolithic OLTP engines cannot meet these requirements, while manually selecting clustering keys across millions of Lakehouse tables does not scale.

## Approach / What changed

The presented work separates serverless PostgreSQL compute from open cloud storage in Lakebase, evolves Spark Structured Streaming with microbatch pipelining and new stateful APIs, automates data clustering through AutoLiquid’s CLUSTER BY AUTO, and uses query history in Ultron to improve optimizer choices. The program also covers LakehouseRT, the Reyden engine, and Enzyme’s incremental view maintenance.

## Takeaways

- Lakebase persists PostgreSQL data and write-ahead logs directly in cloud object storage, providing sub-second cold starts, copy-on-write database branching, and low-latency analytics on live transactional data.
- Spark Structured Streaming’s microbatch pipelining improved throughput by up to 3x; the system also added stateful APIs for complex business logic and fine-grained access control.
- AutoLiquid outperformed customer-selected clustering keys on over 95% of evaluated workloads, while Ultron improved median join latency by 25% in production workloads.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Performance](https://yomu.fyi/topic/performance), [Postgres](https://yomu.fyi/topic/postgres), [Streaming](https://yomu.fyi/topic/streaming)

- Source: [Databricks](https://www.databricks.com/blog/building-ai-era-lakebase-streaming-and-lakehouse-innovations-vldb-2026)
- Source URL: https://www.databricks.com/blog/building-ai-era-lakebase-streaming-and-lakehouse-innovations-vldb-2026
- Ingested by Yomu: 2026-08-30T12:35:06.166Z

[Read original post](https://www.databricks.com/blog/building-ai-era-lakebase-streaming-and-lakehouse-innovations-vldb-2026)