205 AI developers voted in a category where open-source infrastructure meets enterprise governance. Here is what the results reveal.
The March 2026 IT Brand Pulse AI Brand Leader survey asked 205 members of the AI developer community to vote for Market Leader and Intelligence & Innovation Leader in Model Registry Platforms, one of 26 products in the AI Engineering stack. MLflow (Databricks) took the top position in both categories, receiving 30.2% of votes for Market Leader and 27.8% for Intelligence & Innovation Leader. AWS SageMaker (20.0%) and Azure ML (15.1%) followed in Innovation.
The results suggest a consistent but contested leadership position for MLflow across both adoption and innovation. The presence of major cloud providers—AWS SageMaker and Azure ML—in the second tier indicates that model registry functionality is increasingly being bundled into broader MLOps platforms. The IT Brand Pulse analyst team expects model registries to become even more critical as organizations manage growing portfolios of LLMs and agent-based systems.
What Are Model Registry Platforms?
IT Brand Pulse defines Model Registry Platforms as systems that catalog, version, govern, and promote machine learning and AI models across environments and teams. These platforms provide capabilities such as model version control, lineage tracking, approval workflows, metadata management, deployment readiness status, and integration with training, evaluation, and deployment pipelines. Model registries serve as a core control point in MLOps and LLMOps, enabling organizations to manage the lifecycle of models and ensure consistency, compliance, and reproducibility in production. Model Registry Platforms sits within the Operations sub-layer of the broader AI Engineering stack, alongside LLMOps Platforms, AI Observability Platforms, AI Evaluation Platforms, and Experiment Tracking Platforms.
Download the Brand Leader Report for Model Registry Platforms.
