James Curtis is research director of the Data, AI & Analytics channel at at 451 Research from S&P Global Energy Horizons. He also leads the database and data platforms vertical. Previously, he covered business intelligence, analytics and reporting, along with machine learning and data science. James’ current areas of concentration include database and related technology analysis, real-time analytics, cloud computing and cloud-native technologies for database as a service, database optimization tooling, generative AI and retrieval augment generation (RAG) environments, including vector stores and semantic search. James arrived at S&P Global through its 2019 acquisition of 451 Research, which he joined in 2015. Prior to 451 Research, he held several senior roles in technology, marketing and communications. He served as VP of a large BPO firm where he oversaw marketing for analytic solutions. He held senior technical marketing roles at Netezza and later at IBM with responsibility for data warehousing, analytics and big-data products. He has managed global programs at HPE and worked as a case editor at Harvard Business School. James holds a bachelor's degree in English from Utah State University, a master's degree in writing from Northeastern University in Boston and an MBA from Texas A&M University.
At re:Invent 2025, AWS announced new Database Savings Plans for nine services, along with updates spanning Amazon RDS, Amazon OpenSearch Service, Amazon SageMaker and Amazon Redshift. Enabling AI is at the heart of AWS' strategy, but that is only part of the story.
The company offers a unified data intelligence platform that brings together data ingestion, storage, machine learning and geospatial processing. By employing a consolidated, performance-optimized architecture that minimizes infrastructure footprint, Ocient's database blends energy efficiency with high performance.
There are such significant changes going on in how data is managed and in how AI manages data that it is not always clear which requirements are driving which trends. Analyst Jim Curtis returns to discuss data highlights from AWS re:Invent and to identify important changes that are taking place.
The company positions itself as a next-generation in-memory data store designed to handle the massive scale and complexity of modern ML and AI workloads. Dragonfly boasts a multi-threaded architecture that delivers high performance while running on a compact hardware footprint.
This report highlights key topics for 2026 in data, AI and analytics. Generative AI continues to permeate all aspects of the modern IT stack, supporting functions that rely on high-quality data, user-friendly tools and robust infrastructure. While some organizations continue to experiment with GenAI, an increasing number are moving into full-scale adoption and considering the business impacts and outcomes of their GenAI investments.
The cloud sector continues to transform as hyperscalers, managed service providers, global systems integrators, hardware vendors and independent software vendors advance overlapping visions for IT infrastructure and application modernization enabled by automation and powered by the disruptive promise of generative AI. Developer services, integration, automation and business processes take on new importance as modern enterprise IT environments mature and we transition from the "era of cloud" to the "era of AI."
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