211 AI developers voted in a competitive but structured category. Here is what the results reveal about the feature store landscape.
The March 2026 IT Brand Pulse AI Brand Leader survey asked 211 members of the AI developer community to vote for Market Leader and Intelligence & Innovation Leader in Feature Stores, one of 26 products in the AI Engineering stack. Databricks took the top position in both categories, receiving 29.9% of votes for Market Leader and 28.0% for Intelligence & Innovation Leader. AWS SageMaker finished second for Market Leader at 21.8%, while Tecton took second for Innovation at 18.0%.
The results indicate a clear top tier with Databricks holding the strongest overall developer mindshare. While Databricks leads both pillars, innovation is more distributed, with Tecton and Feast contributing significantly to advancing the category. The IT Brand Pulse analyst team expects feature stores to remain a critical MLOps layer as AI systems increasingly require real-time, governed feature pipelines.
What Are Feature Stores?
IT Brand Pulse defines Feature Stores as platforms that manage, transform, store, and serve machine learning features across training and inference pipelines. They provide capabilities such as feature engineering, versioning, lineage tracking, online/offline feature serving, and consistency between training and production environments. Feature stores are a core MLOps component, enabling teams to operationalize machine learning by ensuring that features are reusable, governed, and available in real time for both batch and streaming AI applications. Feature Stores sit within the Data & Retrieval sub-layer of the broader AI Engineering stack, alongside Data Labeling Platforms and Synthetic Data Platforms.
Download the Brand Leader Report for Feature Stores.
