#kinetica-1

#kinetica-1

Apache Kafka has cemented itself as the de facto platform for event streaming, often referred to as the 'universal data substrate' due to its extensive ecosystem that enables connectivity and processing capabilities.

Netskope One AI Security is integrated into the Netskope One platform and designed to protect various components of the AI ecosystem. These include AI applications, AI agents, datasets, and users in both public SaaS environments and private or internally hosted AI systems. Workflows in which autonomous AI agents communicate with other systems are also covered by the security.

Weather impacts sales. Every retailer knows it. But for most, the likelihood that it might rain, snow, or sleet on the third of March somewhere in the Midwest is rarely used. Vendors such as Weather Trends have offered accurate, long-range forecasts for more than 20 years. But the opportunity is not predicting the weather; it's knowing what to do with the data. AI might change that.

Hyperscalers and major data platform vendors offer integrated services across storage, analytics, and model infrastructure. MariaDB's differentiation will likely depend on whether the combined platform can deliver operational speed and simplicity that organizations find easier to run than those larger stacks.

A traveler might search for a weekend getaway and still see travel ads weeks later, long after returning home. The data was right. The timing wasn't.AI-driven marketing has the potential to close that gap - but only if it understands context. Personalization built solely on identity or past behavior can reveal who someone is, but not when or why they're ready to act.As AI takes center stage in marketing strategy, context is emerging as the differentiator that turns reactive automation into predictive intelligence.

Red Hat AI Enterprise provides a foundation for modern AI workloads, including AI life-cycle management, high-performance inference at scale, agentic AI innovation, integrated observability and performance modeling, and trustworthy AI and continuous evaluation. Tools are provided for dynamic resource scaling, monitoring, and security.

Developers have spent the past decade trying to forget databases exist. Not literally, of course. We still store petabytes. But for the average developer, the database became an implementation detail; an essential but staid utility layer we worked hard not to think about. We abstracted it behind object-relational mappers (ORM). We wrapped it in APIs. We stuffed semi-structured objects into columns and told ourselves it was flexible.

Databricks today announced the general availability of Lakebase on AWS, a new database architecture that separates compute and storage. The managed serverless Postgres service is designed to help organizations build faster without worrying about infrastructure management. When databases link compute and storage, every query must use the same CPU and memory resources. This can cause a single heavy query to affect all other operations. By separating compute and storage, resources automatically scale with the actual load.

Snowflake offers a fully managed data platform, but Sumo Logic users often lack insight into performance, login activity, and operational health. The Sumo Logic Snowflake Logs App analyzes login and access activity to identify anomalies or suspicious behavior. It also optimizes data pipelines with insights into long-running or failing queries. Teams can centralize log data to facilitate correlation across applications, cloud services, and data platforms.

With the introduction of Live Query for BigQuery and Alteryx One: Google Edition, users no longer need to move data to run workflows. Companies that standardize cloud platforms for analytics and AI often see a gap between where data is stored and how it is prepared and used. Alteryx wants to change that by bringing analytics workflows directly to BigQuery. The promise: from data to insight to action, without compromising on security or scalability.

"Pyramid adds an analytics and semantic layer that can define metrics in a way that both humans and AI agents can rely on,"

Before the acquisition, Koyeb's platform already helped users deploy models from Mistral and others. In a blog post, Koyeb said its platform will continue operating. But its team and technology will now also help Mistral deploy models directly on clients' own hardware (on premises), optimize its use of GPUs, and help scale AI inference - the process of running a trained AI model to generate responses - according to a press release from Mistral.

The rise of generative AI is often seen as an existential threat to the SaaS model. Interfaces would disappear, software would fade away, and existing players would become irrelevant. However, new figures from Databricks paint a different picture. Rather than undermining SaaS, AI appears to be increasing its use. This week, Databricks reported a revenue run rate of $5.4 billion, a 65 percent year-on-year increase. More than a quarter of that now comes from AI-related products.