Starburst Recognized as a Leader in the 2025 GigaOm Lakehouse Report

/ AI, Data Analytics, Infrastructure
Starburst Recognized as a Leader in the 2025 GigaOm Lakehouse Report

The News

Starburst has been named both a Leader and a Fast Mover in the 2025 GigaOm Radar for Data Lakes and Lakehouses, marking its third consecutive year earning a top position. The report highlights Starburst’s product capabilities, AI readiness, and continued momentum in driving open, scalable data architectures.  

To read more, visit the full report here.

What We Think

The data lakehouse model has evolved into a strategic cornerstone for organizations by combining analytics and AI. Developers today need platforms that support flexible, query-in-place access to heterogeneous data across cloud, on-premises, and hybrid environments. According to theCUBE Research, developer teams are pushing for open data architectures that reduce movement, simplify governance, and support AI readiness. Starburst’s recognition as a GigaOm Leader may affirm its alignment with these needs, especially as AI model development demands scalable, federated data access and near-real-time performance.

Starburst’s ability to execute on an open lakehouse strategy, backed by Trino and support for federated SQL, could mean developers can access and analyze distributed data without copying or restructuring it. This capability is important for app developers and ML engineers working with mixed workloads across Delta Lake, Iceberg, Hudi, and cloud object storage. GigaOm’s high AI readiness score signals that Starburst isn’t just analytics-focused but is positioned as an AI infrastructure layer, with data cataloging, governance, and performance optimization tooling that supports AI/ML model lifecycle requirements.

Traditional Data Platforms Have Lagged on AI Readiness

Developers are faced with data platforms that silo storage by workload type (BI, data science, streaming) and force data duplication to run queries at scale. As enterprises shift toward AI-driven apps and intelligent services, those legacy systems introduce bottlenecks. Starburst’s federated approach could challenge that model by enabling cross-platform analytics without migration or ETL overhead. The company’s focus on open formats and hybrid deployment flexibility could remove many of the blockers associated with proprietary, cloud-locked warehouse platforms.

AI Readiness Becomes the New Benchmark for Data Platforms

GigaOm’s AI readiness scoring framework, which measures how platforms support AI/ML and generative AI workloads, is likely important to developers who need infrastructure that scales with intelligent applications. Starburst’s strong marks in this area reflect its approach to unifying data governance, accelerating model development, and serving insights across teams without sacrificing openness. This is vital for modern app stacks that embed predictive analytics, recommendation engines, or large-scale semantic search, as they all use cases where Starburst’s architecture provides measurable developer value.

What’s Next?

Enterprise adoption of lakehouse platforms can be expected to accelerate as AI becomes a core competency across industries. According to industry research, 60% of enterprises will deploy AI-ready data architectures by 2026 to support model operationalization and real-time analytics. Starburst’s continued leadership in the GigaOm Radar suggests it is well-positioned to lead this shift, particularly for organizations prioritizing open standards, hybrid cloud, and query performance.

Looking forward, we might see Starburst expand its focus on GenAI-specific optimizations, tighter integrations with orchestration platforms like Kubernetes and Airflow, and enhanced developer tooling for pipeline observability and governance. For developers building intelligent applications, Starburst presents a validated, scalable foundation to support innovation at both the query layer and AI pipeline level.

Authors

  • Paul Nashawaty

    Paul Nashawaty, Practice Leader and Lead Principal Analyst, specializes in application modernization across build, release and operations. With a wealth of expertise in digital transformation initiatives spanning front-end and back-end systems, he also possesses comprehensive knowledge of the underlying infrastructure ecosystem crucial for supporting modernization endeavors. With over 25 years of experience, Paul has a proven track record in implementing effective go-to-market strategies, including the identification of new market channels, the growth and cultivation of partner ecosystems, and the successful execution of strategic plans resulting in positive business outcomes for his clients.

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  • With over 15 years of hands-on experience in operations roles across legal, financial, and technology sectors, Sam Weston brings deep expertise in the systems that power modern enterprises such as ERP, CRM, HCM, CX, and beyond. Her career has spanned the full spectrum of enterprise applications, from optimizing business processes and managing platforms to leading digital transformation initiatives.

    Sam has transitioned her expertise into the analyst arena, focusing on enterprise applications and the evolving role they play in business productivity and transformation. She provides independent insights that bridge technology capabilities with business outcomes, helping organizations and vendors alike navigate a changing enterprise software landscape.

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