What AI says about Feast
Feast is an open-source feature store that manages and serves structured data for model training and inference.
AI calls itopen-source,lightweight,flexible,cloud-agnostic,widely adopted,modular
Since Jul 5Updated Nov 11, 2026Based on 26,097 AI answers
Reviewed by Dimitry Apollonsky
Mentioned in · Public index
1%
of AI answers about Feast and its rivals · since Jul 5
Based on 26,097 AI answers
- ChatGPT1%
- Google AI Mode1%
How often AI mentions Feast
of AI answers about Feast and its rivals
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Sep 14OctNov 2
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Markets where AI mentions Feast
Mentioned inLowHighFew answers
All marketsChatGPTGoogle AI Mode
- Machine Learning Feature Store PlatformsChatGPTGoogle AI Mode
- Customer Data Platforms & Churn PredictionOutside both engines’ top 25
- Model Drift Monitoring & Retraining ToolsOutside both engines’ top 25
- Enterprise MLOps Model Registry PlatformsOutside both engines’ top 25
- MLOps and Data Orchestration PlatformsOutside both engines’ top 25
- Predictive Churn Analytics SoftwareOutside both engines’ top 25
- RLHF Data Collection & Training PlatformsOutside both engines’ top 25
- Business Intelligence & Analytics SoftwareOutside both engines’ top 25
- Data Annotation Platforms and ServicesOutside both engines’ top 25
Topics where AI mentions Feast
TopicMentioned in · on this topicRank
- Most mentionedMentioned in
- What's the best feature store for serving real-time features to ML models?on this questionFeast shares the lead for mentions with 1 more97%
Excerpts where Feast appeared in the AI's answer
Google AI ModeSep 18, 2026, Google AI Mode Feast (Open Source ): The most widely adopted open-source, lightweight feature store.
ChatGPTSep 14, 2026, ChatGPT Feast is the better choice if you want an open-source abstraction and are comfortable assembling the infrastructure yourself.
Feast in AI answers
1 of 8
Which platform is the best for building and managing a feature store that integrates with both batch and real-time systems?
ChatGPTChatGPT· Sep 21, 2026
Feast is the better architectural fit when you want open source, cloud portability, and control over the underlying infrastructure.
Google AI ModeGoogle AI Mode· Sep 21, 2026
Feast (Best Open-Source / Zero Vendor Lock-in Option): Feast is the most widely adopted open-source feature store .
Sites AI cites
- Your site21%
- Introduction | Feast: the Open Source Feature Store (opens in a new tab) · 4%
- Overview | Feast: the Open Source Feature Store (opens in a new tab) · 3%
- Introduction | v0.22-branch | Feast: the Open Source Feature Store (opens in a new tab) · 3%
- Overview | Feast: the Open Source Feature Store (opens in a new tab) · 2%
- Quickstart | Feast: the Open Source Feature Store (opens in a new tab) · 2%Leaves Feast out
- Quickstart | Feast: the Open Source Feature Store (opens in a new tab) · 1%
- Introduction | master | Feast: the Open Source Feature Store (opens in a new tab) · 1%
- Quickstart | v0.26-branch | Feast: the Open Source Feature Store (opens in a new tab) · 1%
- Feature Serving and Model Inference | master | Feast: the Open Source Feature Store (opens in a new tab) · 1%
- Overview | Feast: the Open Source Feature Store (opens in a new tab) · 1%
- 9%
- Feature Store Comparison: Feast vs Tecton vs Databricks [2026] | Tacnode Blog (opens in a new tab) · 8%
- Feature Store Comparison: Feast vs Tecton vs Databricks [2026] | Tacnode Blog (opens in a new tab) · 1%
- What Is a Feature Store? Architecture, Benefits, and How It Prevents Training-Serving Skew | Tacnode Blog (opens in a new tab) · <1%
- 9%
- GitHub - feast-dev/feast: The Open Source Feature Store for AI/ML · GitHub (opens in a new tab) · 6%
- feast/docs/getting-started/architecture/overview.md at master · feast-dev/feast · GitHub (opens in a new tab) · 1%
- feast/docs/getting-started/quickstart.md at master · feast-dev/feast · GitHub (opens in a new tab) · 1%
- feast/docs/getting-started/architecture/feature-transformation.md at master · feast-dev/feast · GitHub (opens in a new tab) · <1%
- feast/docs/getting-started/components/online-store.md at master · feast-dev/feast · GitHub (opens in a new tab) · <1%
- Your site7%
- Leaves Feast out6%
- A Deep Dive into Feature Stores. Feature stores are the “heart” of any… | by Samuel Taiwo | Medium (opens in a new tab) · 1%
- MLOps with a Feature Store. TLDR; If AI is to become embedded in… | by Fabio Buso | Feature Stores for ML | Medium (opens in a new tab) · 1%
- Medium (opens in a new tab) · 1%Leaves Feast out
- Enabling highly scalable feature store with Teradata Vantage and FEAST (opens in a new tab) · 1%
- Medium (opens in a new tab) · <1%
- A Practical Guide to Feature Stores for Data Engineers | by Kazim Musa | Medium (opens in a new tab) · <1%
- MLOps 03: Feast Feature Store — An In-depth Overview Experimentation and Application in Tabular data | by Ong Xuan Hong | Medium (opens in a new tab) · <1%
- A Beginner’s Guide To Understanding Feature Stores | by Gavita Regunath | Advancing Analytics | Medium (opens in a new tab) · <1%
- Architectures for Data Scientists and Big Data Professionals | by sharmi hacks | Feature Stores for ML | Medium (opens in a new tab) · <1%
- Choosing a Feature Store: Feast vs Hopsworks | by Markus Schmitt | TDS Archive | Medium (opens in a new tab) · <1%
- 4%
- Building Real-Time ML Features with Feast, Spark, Redis, ... (opens in a new tab) · 2%
- Online Databricks Feature Store for Real-Time Inferencing (opens in a new tab) · 1%
- Building Real-Time ML Features with Feast, Spark, Redis, and ... (opens in a new tab) · 1%
- Learn how to build your own lightweight feature store and ... (opens in a new tab) · <1%
- Building Production-Ready Recommender Systems with Feature Stores (opens in a new tab) · <1%
- From Real-Time ML to Agents with Hopsworks - Feature Store Summit 2025 (opens in a new tab) · <1%
- Building a feature store on GCP with BigQuery (opens in a new tab) · <1%
- Building Real-Time ML Features with Feast, Spark, Redis, ... (opens in a new tab) · <1%
- Leaves Feast out3%
- Databricks Feature Store | Databricks on AWS (opens in a new tab) · 2%Leaves Feast out
- Databricks Feature Store overview and glossary | Databricks on AWS (opens in a new tab) · 1%Leaves Feast out
- 3%
- Feature Stores for Real-time AI/ML: Benchmarks, Architectures, and Case Studies | Redis (opens in a new tab) · 1%
- Feature Stores Explained: The Three Common Architectures (opens in a new tab) · 1%
- Redis Feature Store (opens in a new tab) · 1%
- Introduction to Feast: Building fast feature stores with Redis (opens in a new tab) · <1%
- Redis Feature Store (opens in a new tab) · <1%
