Gartner Expert

Aaron Rosenbaum is an Analyst on the Data Management team focusing on cloud data lakehouses, analytical and operational DBMS, and AI-ready data architectures. He guides enterprise IT leaders through evaluating converged data platforms and transitioning from legacy systems to cloud-native solutions like Databricks, Snowflake, and native cloud service provider offerings.

Reflecting his primary research focus, Aaron is the lead author for the Data Lakehouse Platforms Magic Quadrant

He also leads foundational research on the architectural shifts driven by Python, Spark, and open table formats (such as Apache Iceberg) as well as use of Agentic AI for data management.

Additionally, he is a co-author of the legacy Cloud DBMS Magic Quadrant, the Critical Capabilities for both Analytical and Operational DBMS, and the Data Management Hype Cycle and is a co-author of the new Operational Database Magic Quadrant.

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Aaron handles a significant volume of client inquiries and proposal reviews regarding database pricing, FinOps, and contract negotiations. Drawing on this large case volume, he is the lead author of research on best practices for negotiating and managing Snowflake contracts. He regularly advises sourcing and IT leaders on benchmarking enterprise discounts, optimizing consumption-based cloud spend, and restructuring commitments with vendors such as Snowflake, Databricks, Cloudera, and MongoDB.

Furthermore, Aaron advises clients on operational database modernization, including migrating high-stakes workloads from on-premises legacy systems to cloud-native or open-source relational and non-relational alternatives.

His coverage also extends to helping organizations prepare their data ecosystems and semantics for generative AI, natural language querying, and agentic workflows.

Previous experience

Professional background