Salvatore Salamone

Cloud databases are evolving from static storage systems into active enablers of AI applications. Learn how vector search, real-time streaming, and multi-model capabilities are reshaping database strategies.

Neocloud providers are filling the need for fast and affordable access to the GPUs that enterprises need to support their AI efforts.

Cloud is a strategic asset rather than just a technical choice. These 2025 cloud trends underscore the shift from purely technical optimization to holistic business enablement.

Hybrid and multi-cloud data replication must address latency, consistency, security, interoperability, and cost challenges. Streaming, if adopted properly and implemented intelligently, can help in all of these areas.

Most organizations today cannot lean on just one or two data management solutions. What’s needed is a multi-tech data platform that ensures performance, security, and more.

As data becomes more complex, the need for a multi-tech platform has never been more evident. By looking beyond single solutions like Apache Cassandra or Apache Kafka and embracing a more holistic, integrated approach, businesses can future-proof their data strategies and stay competitive in an ever-evolving landscape.

Announcements from the conference put teeth into Red Hat’s approach to AI and automation. Similar to what was done with cloud and open source, Red Hat is now doing the same for AI with a platform for AI approach.

Instaclustr’s managed service allows companies to deploy a center Apache Cassandra across multiple clouds without setting up hardware or software.

The key to any successful migration to Open Source Apache Cassandra is careful planning to keep any disruptions and downtime to an absolute minimum.

As is the case in other industries, travel industry businesses do not have the time or resources to manually cobble together data pipelines for every use case and every application as each emerges.

Automated data pipelines address or completely eliminate most of the common factors that can impact data quality.

ESG found that automated data pipelines deliver a number of time and cost savings benefits.