Databricks unveils Omnigent and LTAP at Data + AI Summit 2026

Chinese Premier Li Qiang on Wednesday warned of "serious consequences" if governments fail to step up regulation of artificial intelligence as he addressed the World Economic Forum in Dalian, known as the "summer Davos".

Separating transactional databases from analytical systems was, until recently, considered good architecture. Now, as enterprises adopt AI agents that continuously read, reason over, and act on business data, data warehouse and database vendors are increasingly deciding that separation has become a liability. Just weeks after Databricks unveiled its Lakehouse Transaction and Analytical Processing (LTAP) offering based on Neon Postgres to bring operational (OLTP) and analytical (OLAP) processing closer together, EnterpriseDB (EDB) has introduced converged analytics capabilities for its managed EDB Postgres AI database service with the same intent. Both vendors are responding to the same pressure of enabling AI agents for enterprises to operate on fresh operational data without waiting for pipelines and replicas, but EDB argues its approach starts from a fundamentally different place. “Databricks is building from the lakehouse outward, trying to pull transactional capability in through L

Anthropic's rapid rise has sparked a power struggle with the Trump administration over AI regulation, national security and control of advanced models. The clash threatens its IPO, highlights gaps in AI governance, and raises a bigger question: who should control transformative AI technology?

Databricks' choice to remain private highlights a strategic shift in tech firms prioritizing long-term growth over immediate public market pressures. The post Databricks opts for private funding over IPO amid market lull appeared first on Crypto Briefing.

Databricks is pitching a fix for what it sees as the growing operations mess in enterprise AI. With the launch of Genie ZeroOps, unveiled at its Data + AI Summit, the company is targeting a problem many data teams know too well: it’s no longer building pipelines and models that hurts, it’s keeping them running. As data estates sprawl and AI workloads multiply, engineering time is increasingly eaten up by maintenance. Meanwhile, AI coding tools are accelerating development, churning out even more assets that need oversight, widening the gap between how fast teams can build and how much they have to manage. Databricks Genie ZeroOps is a new agentic operations capability that is designed to automate the monitoring, investigation, and remediation of issues across data and AI workloads. Currently in private preview, ZeroOps uses an AI agent to identify anomalies, trace root causes using metadata and lineage information via Unity Catalog, generate proposed fixes, and then test those fixes in

Beth Tschida, who became Jamf CEO in May after serving as CTO and as interim CEO, is the first woman to lead the company in its near 25-year history. I spoke with her this week at the London Jamf Nation event, where the company introduced its new AI Governance solution. How the transition to CEO is going  “It’s been a great privilege and an adjustment,” she said. “Jamf has always been a company deeply focused on culture, which is exactly why I love being here. Having the ability to influence and improve that culture from this role is something I feel very supported in doing.” The last few years have seen a variety of changes at Jamf, which was briefly a public company. “We’ve come through a period of change, not all of it easy,” Tschida said. “But we now have a great partnership with Francisco Partners. We’re private, we’re focused on solving customer problems, and we’re finding ways to lean into what we’re good at.” Women in tech and mentorship Tschida is a good choice to lead a softw

First came vector databases, then RAG. Now, the next frontier in enterprise AI is taking shape: context layers that give autonomous agents a shared understanding of the business, a vision Databricks is advancing with Genie Ontology. Currently in preview, Genie Ontology automatically extracts business context from enterprise data, dashboards, queries, pipelines, documents, and applications and organizes it into a living graph that AI agents can use to understand how an organization operates. Showcased at the company’s Data + AI Summit, Genie Ontology uses a ranking system inspired by Google’s PageRank to identify the most authoritative business definitions within an organization. Rather than treating all sources equally, it weighs factors including who created the information, how widely it is used, its links to certified datasets and assets, and how recently it was updated before determining which answer an AI agent should rely on, Databricks CEO Ali Ghodsi said during his keynote late

Databricks' rapid AI-driven growth highlights the tension between scaling innovation and maintaining profitability, impacting future investment strategies. The post Databricks sales growth tops 80% as margins shrink from AI costs appeared first on Crypto Briefing.