Neon vs OVHcloud

Databricks Powers Agentic Future with $7B Run Rate

Databricks, the data and AI company, has revealed it has surpassed a $7 billion revenue run rate, growing 80% year-over-year, and is valued at $190 billion. The company, which began as a Spark-based data processing platform, has evolved through multiple technology S-curves—Spark, Lakehouse, Lakebase, and now AI agents. Databricks' Lakehouse architecture unifies data lakes and warehouses, while its new Lakebase product, built on the acquisition of Neon, brings operational databases onto the same lakehouse foundation. The company is positioning itself as the 'system of record for agents,' with tools like Genie and Agent Bricks enabling employees to build and manage AI agents. With over 17 million databases launched by agents daily, Databricks is betting on the rise of agentic automation transforming the nature of work and the structure of firms, shifting from managerial hierarchy to human-agent collaboration.

• Databricks surpassed $7 billion revenue run rate, growing 80% year-over-year.
• Databricks is valued at $190 billion.
• More than 17 million databases are launched by AI agents on Databricks every day.

Major update to our Free Plan: now with 1 GB of Postgres storage per project, 100 projects included

Database storage on the Neon Free plan is now 1 GB per project, up from 0.5 GB. You still get 100 projects, with existing projects getting the new limit automatically.

Claimable Neon: Provisioned by agents, claimed by humans

Claimable Neon implements the anonymous registration method in auth.md, the open agent registration protocol authored by WorkOS, to give agents a way to provision a temporary Neon project without creating an account or collecting payment details.

Adtech AI Infrastructure Costs Challenge Profitability

This article explores the financial and operational challenges that AI adoption brings to adtech infrastructure. It argues that as AI workloads move from experimentation to production, the associated compute, storage, and network costs become significant and can erode product margins. The piece emphasizes the need for adtech companies to optimize infrastructure economics, match resources to workloads, and consider data residency requirements. It highlights the tension between model sophistication and real-time performance, and the importance of architectural flexibility. The author, Jeffrey Gregor from OVHcloud, positions infrastructure strategy as a key competitive differentiator in the next phase of adtech, where the ability to run AI efficiently and economically at scale matters more than access to AI itself.

• IDC predicts that by 2030, autonomous AI agents will manage a significant share of enterprise advertising operations.
• The article is authored by Jeffrey Gregor, General Manager at OVHcloud US.
• OVHcloud is a global cloud provider and subsidiary of OVH Group SAS.