Paxata Unveils Spring Release of Adaptive Information Platform

In this week’s real-time analytics news: Qlik introduced a sovereign AI initiative and an expansion of its trust and governance capabilities for AI.

In this week’s real-time analytics news: StreamNative introduced Lakestream, a new architectural paradigm for lakehouse-native streaming.

As the pace and complexity of operations accelerate, organizations are rethinking architectures to enable real-time, human-in-the-loop decision-making.

The edge is where it all happens. It is where innovation is created and where it is delivered. SQL Server workloads must therefore be just as resilient and highly available there as they are in the cloud or in a traditional data center.

Modern enterprise applications, especially those driven by real-time data, AI inference, and latency-sensitive user experiences, are exposing the limitations of a one-size-fits-all cloud strategy, forcing organizations to rethink workload placement across hybrid and distributed environments. The shift is no longer about “cloud vs. on-prem,” but about architecting for performance, cost predictability, and data gravity in a world where systems must operate continuously and adapt dynamically.

The AI revolution isn’t happening in GPUs or model architectures. It’s happening quietly in the data pipelines that feed them.

The future of AI in the enterprise is recognizing that intelligence, whether human or artificial, must be governed by clear, written code.

Graph technology expert Dominik Tomicevic on why Anthropic’s model context protocol offers a much stronger way for LLMs to connect with the outside world than previous approaches, but it needs the helping hand of graph technology and GraphRAG.