Entries by Catie Merrill, Senior Analyst

Agentic AI Adoption Is Pressuring Security Architectures to Converge

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The emerging pattern of multicloud security consolidation has direct implications for both Amazon Web Services (AWS) and Microsoft, as enterprises reassess detection pipelines, governance models and operating frameworks heading into 2026. Although AWS remains well positioned in analytics-heavy workloads, the company needs to reevaluate its long-established “building block” approach, especially as peers deliver more integrated platforms. For Microsoft, its strengths will continue to be with organizations where Microsoft 365 already anchors their identity and collaboration strategies.

Oracle’s Full-stack Strategy Underscores a High-stakes Bet on AI

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Though not immune to the risks and uncertainties of the AI market at large, Oracle is certainly executing, with the bulk of revenue from AI contracts already booked in its multibillion-dollar remaining performance obligations (RPO) balance. And yet, as OCI becomes a more prominent part of the Oracle business, big opportunities remain for Oracle, particularly in how it partners, prices and simply exists within the data ecosystem.

Modernization First: Mongo’s Enduring Pursuit of the AI Opportunity

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Agentic AI has customers and ecosystem participants reconsidering the role of the database. MongoDB is well positioned to capitalize on the AI opportunity, partly due to its JSON-native document database, as well as its early support for native vector search in the cloud. But for customers using legacy systems, there is still much work to be done in preparing for AI, and this is where MongoDB’s investment priorities lie.

Oracle Strategy: Large Backlog and New Government Contracts Boost Vendor’s Long-term Outlook

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Oracle’s current business strategy centers on streamlining customer success efforts, enhancing partner collaboration, and expanding multicloud infrastructure. By consolidating its services under the Oracle Customer Success Services (CSS) umbrella, the company has improved life cycle support for clients, reduced overlap with systems integrators, and equipped partners with tools like the Cloud Success Navigator to enhance implementation and renewal outcomes.

Data Quality & Governance Pillars, and Ecosystem-led Approach Mark Informatica’s Entry Into Agentic AI

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Between the technology partners and GSIs, Informatica works with a robust ecosystem of partners in a triparty approach, where resources from a hyperscaler, GSI and Informatica are brought together to help customers modernize their data faster and, by default, hasten AI’s time to value. When we survey and speak to alliance decision makers at IT services firms, data management comes up as one of the top areas for partner-led growth, signaling to the ecosystem that they will continue to invest in resources to guide conversations with customers with the technology maturity to address the data foundations ahead of GenAI.

Oracle Redefines Data Intelligence in Full-stack Approach

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Oracle’s full-stack approach to analytics makes a compelling case for consolidation, helping partners create value by eliminating disparate integrations and unlocking ROI. This is particularly true for partners that are perhaps willing to abandon the typical tech-agnostic approach and recommend Oracle as the primary choice from a data and analytics perspective. If Oracle engages a broader external data ecosystem in the future, as discussed above, partners will need to make sure they look beyond the applications layer and leverage Oracle’s broad PaaS and IaaS capabilities for custom development use cases.

Google Cloud Cements Values of Enterprise Readiness, Full-stack AI and Hybrid Cloud at Next 2025

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When discussing Google Cloud’s three key attributes, Kurian first highlighted how Google Cloud Platform (GCP) is optimized for AI. Based on our own conversations with IT decision makers, this claim is valid: many customers enlist GCP services purely for functional purposes, as they believe they cannot obtain the same performance with another vendor. This is particularly true of BigQuery, for large-scale data processing and analytics, and increasingly Vertex AI, which now supports over 200 curated foundation models for developers.