Databricks says AI agents disrupt database separation
Databricks claims that autonomous AI agents are forcing a shift in traditional database design, breaking down the longstanding separation between systems for operational and analytical workloads. The company says its LTAP approach unifies these workloads not by combining their engines, but by providing a shared storage layer that can handle both fast transactions and large-scale analysis.
- Databricks proposes Lakebase's LTAP architecture as a solution
- LTAP uses unified storage, not a single engine
- Traditional databases separate operational and analytical tasks
- AI agents' needs reportedly overwhelm old database designs
Sources covering this
In this story
More in Enterprise
Red Hat adds NVIDIA BlueField to OpenShift
Red Hat OpenShift will now support NVIDIA BlueField hardware, aiming to make data centers faster by letting specialized cards take on tasks usually handled by main processors. By moving network traffic management and security enforcement off CPUs and onto BlueField, businesses can free up computing power for core applications and AI tasks. Red Hat says this helps cut operational costs and makes network security more robust.
Google Data Cloud adds new AI and analytics tools
Google just launched several new features for its Data Cloud. BigQuery now supports stateful processing in streaming queries, letting you do things like rolling averages in real time (currently in preview). There’s also a ready-to-use synthetic data generator for Managed Kafka, now generally available. And Lakehouse managed tables for Apache Iceberg are in preview, promising easier data management and cross-tool compatibility. Updates to Dataflow pipelines are also rolling out.
GitLab Duo Self-Hosted supports multiple AI models via Azure
GitLab is letting organizations use its AI coding features with their own choice of large language models, including OpenAI, Anthropic, Meta, and Mistral, when deployed through Microsoft’s Foundry platform on Azure. Companies can now pick which region, network, and cloud controls handle their code—with model assignments down to the individual feature. This helps teams meet data residency and compliance needs.
Salesforce launches new Agentforce bundles with built-in AI
Salesforce just unveiled three bundled versions—Core, Advanced, and Max—of its Agentforce tools for sales, service, and industry customers. These bundles now include built-in AI, Slack, upgraded analytics, enterprise-level security, and customer support, all for a single price. The Max edition, according to Salesforce, offers 60% more value than the previous Agentforce 1, with existing customers able to upgrade at no extra charge.