We're excited to share that Cube has been recognized as a Leader and Outperformer in the 2025 GigaOm Radar for Semantic Layers and Metrics Stores. This recognition positions Cube in the Innovation/Platform Play quadrant, reflecting our commitment to rapid innovation and comprehensive platform capabilities that serve the evolving needs of data teams navigating the transformation from traditional BI to agentic analytics.

The AI-Driven Future of Data Applications

This recognition comes at a pivotal moment. We believe AI is fundamentally transforming the landscape of data tools, and the semantic layer has never been more critical. As organizations move from traditional business intelligence toward what we call "Agentic Business Intelligence," the need for a trusted, governed foundation becomes paramount.

GigaOm's analysis highlights what makes Cube uniquely positioned for this transformation: our ability to serve as a foundation for embedded analytics, accelerate AI-augmented BI workflows, enable modern agentic analytics applications, and deliver all of this through a developer-friendly, API-first platform with intelligent caching and pre-aggregation.

The report emphasizes Cube's versatility across the modern data stack—from standardizing metrics in business intelligence to enabling real-time analytics and building embedded analytics applications. This breadth, combined with Cube's advanced data modeling capabilities and comprehensive API support (REST, GraphQL, SQL, MDX and DAX), positions Cube as a universal semantic layer that can power any data application: internal, external, human, or AI-driven.

Why Semantic Layers Matter More Than Ever for AI

While AI can dramatically increase productivity and lower barriers to analytics, it also introduces new risks around data quality and governance. This is precisely where semantic layers become indispensable. A semantic layer provides the "safe zones" that AI agents need—governed, trusted definitions that prevent hallucinations and ensure accurate insights.

At Cube, we've seen this firsthand. Almost every organization wants a semantic layer; the challenge has always been the complexity of building and maintaining one. Now, with AI, we can significantly streamline this process. AI can handle mundane tasks, assist with modeling, and act as an intelligent guide—but it needs the semantic layer as its foundation to deliver trustworthy results.

This is why we've evolved from being a headless semantic layer to building our own native AI/BI frontend. We're applying AI across all three core BI functions—Modeling, Exploration, and Presentation—while maintaining human oversight and control at every step.

What Sets Cube Apart

GigaOm scored Cube highly across multiple critical areas:

Modeling Language Support
Cube's declarative YAML syntax combined with JavaScript and Python support for complex modeling gives data engineers the flexibility they need. Whether you're building straightforward metrics or dynamic data models, Cube provides the right tools for the job—and now, with Cube Copilot, AI assistance to accelerate the process.

Advanced Data Modeling Capabilities
From multiple fact tables and many-to-many relationships through bridge tables to polymorphic cubes for parent-child relationships, Cube captures complex business logic that reflects real-world data scenarios. This richness in the semantic layer becomes the context that powers accurate AI-driven insights.

DataOps Integration
With deep Git integration across major providers, Cube enables version control, pull requests, CI/CD, and separate development, staging, and production environments. Your semantic layer models benefit from the same software engineering best practices you apply to application code—critical as AI starts generating and modifying these models.

Native API Support and Caching
Cube's comprehensive API offerings, including REST, GraphQL, SQL, MDX and DAX, ensure seamless connectivity with your existing tools and workflows. Combined with Cube's intelligent pre-aggregation and caching layer, queries are accelerated dramatically, providing the performance AI applications and BI tools demand.

Why We're an Outperformer

The Outperformer designation recognizes our ambitious roadmap and rapid pace of innovation. Over the past year, we've launched transformative capabilities including a Visual Modeler for no-code data modeling, AI assisted data model generation, DAX support and first class integrated AI/BI capabilities. We've also introduced next-generation capabilities with our Tesseract data modeling engine and expanded our integration ecosystem.

This momentum continues to accelerate. We're continuing to develop our agentic AI features that enable users to interact with their data through natural language, powered by AI agents tailored to different personas—data analysts, data scientists, and data engineers. Our new native AI/BI frontend represents a fundamental shift in how organizations will work with data, augmenting human intelligence at every stage of the analytics workflow.

The goal isn't to replace data professionals, it's to amplify their capabilities and make analytics accessible to a broader range of knowledge workers. With AI handling mundane tasks and providing intelligent assistance, data teams can move faster while maintaining the governance and accuracy that only a well-designed semantic layer can provide.

Looking Ahead: Agentic Business Intelligence

The GigaOm Radar report arrives as we're witnessing a transformation in how organizations approach analytics. Traditional BI isn't disappearing, it's evolving into Agentic Business Intelligence, where AI augments modeling, exploration, and presentation workflows while humans maintain fine-grained control over every AI action.

Cube provides the essential foundation for this evolution. As organizations face increasingly decentralized data and the growing complexity of AI/BI initiatives, the need for a universal semantic layer has never been clearer. Cube helps eliminate confusion, standardize metrics, and deliver trusted data to any endpoint—whether that's a BI tool, an embedded analytics application, or an AI agent.

GigaOm identifies areas where Cube continues to evolve, particularly around GenAI enablement. While our agentic features are actively in development, our existing platform already empowers teams to enrich LLMs with appropriate business context and complex logic captured in semantic models. As these capabilities reach general availability, they'll further strengthen Cube's position as the platform that bridges traditional BI and the AI-driven future.

Use Cases Where Cube Excels

The report highlights several areas where Cube delivers exceptional value:

  • Standardizing metrics across business intelligence and reporting, ensuring consistency for both human analysts and AI agents
  • Enabling embedded analytics with developer-friendly APIs and comprehensive integration options
  • Powering agentic analytics applications with a trusted semantic foundation that prevents AI hallucinations
  • Accelerating query performance through intelligent pre-aggregation and caching

Try Cube Today

Whether you're looking to standardize metrics across your organization, build embedded analytics experiences, or prepare your data infrastructure for AI-driven applications, Cube provides the foundation you need.

For a comprehensive look at Cube's evaluation and to understand how semantic layers fit into modern data architectures, we encourage you to read the complete GigaOm Radar report.

Thank you to the entire Cube community—our users, partners, and contributors—for making this recognition possible. Your feedback and collaboration continue to drive our innovation forward as we build the future of Agentic Business Intelligence together.

Ready to see what Cube Cloud can do for your organization? Get started today or contact our team to learn more about how Cube can power your AI/BI transformation.