Feature stores companies, products & suppliers
Serving and governing ML features for training and inference. Jobs: offline feature compute; online feature serving; point-in-time correctness.
What are Feature stores?
Serving and governing ML features for training and inference. Jobs: offline feature compute; online feature serving; point-in-time correctness.
What problems does it solve?
Training and serving use different feature code, so models silently skew.
Typical business use cases
- Offline feature compute
- Online feature serving
- Point-in-time correctness
Important capabilities
- Feature defs
- Serving API
- Lineage
What buyers should evaluate
- Point-in-time joins
- Access to features
- PII in features
Risks and governance considerations
Features that encode prohibited attributes.
Procurement checklist
- Feature catalogue
- Access
- Point-in-time tests
Relevant AI Trustmark assurance
AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.
Companies and providers
Claimed suppliers appear first so buyers can start with listings the company has taken ownership of. Payment does not buy this order.
Amazon Web Services is Amazon's cloud division selling compute, storage, Bedrock model hosting and related AI infrastructure. Public pages cover regional cloud services for builder
Drive innovation in your enterprise with trusted open source from Canonical — simple, cost-effective, and supported. Canonical publishes Charmed Feast as named AI products. C
Chalk is the AI data platform that delivers real-time context and compute infrastructure for agents and ML models — deployed in your cloud, built for speed. Chalk publishes Chalk F
Mosaic AI on Databricks unifies model building, evaluation, serving, and governance on the lakehouse. Public marketing also emphasises lakehouse-native GenAI/ML. It is presented fo
Google is a US technology company that sells consumer and cloud AI products, including Gemini, Search, and related developer APIs on Google Cloud. Google publishes Imagen, Gemini f
Build, deploy, and scale production ML systems with Hopsworks. The Feature Store and MLOps platform for real-time AI, trusted by leading teams. Hopsworks publishes Hopsworks Featur
JFrog publishes JFrog ML and JFrog Xray as named AI products. JFrog is used for Model / data poisoning detection and Feature stores work. JFrog is recorded in Israel. JFrog publish
Microsoft Corporation sells Windows, Azure, Microsoft 365 and Copilot AI products. Public pages cover cloud, productivity and developer APIs used by enterprises and consumers. Micr
Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps. Redis publishes Redis Feature Form as named AI products. Redis is used f
Snowflake Cortex brings LLM and ML functions into the Snowflake Data Cloud for governed SQL/AI analytics. Public marketing also emphasises aI in-warehouse with Snowflake governance
Databricks offers a unified platform for data, analytics and AI. Simplify ETL, data warehousing, governance and AI on the Data + AI Platform. Tecton is used for Feature stores work
Products
Claimed products appear first. Ranking packs and payment do not change this list.
- Amazon SageMaker Feature Store· Amazon Web Services
- Azure Managed Feature Store· Microsoft
- Chalk Feature Store· Chalk
- Charmed Feast· Canonical
- Databricks Feature Engineering· Databricks
- Hopsworks Feature Store· Hopsworks
- JFrog ML· JFrog
- Redis Feature Form· Redis
- Snowflake Feature Store· Snowflake
- Tecton· Tecton
- Vertex AI Feature Store· Google
Related categories
Relevant procurement and assurance guides
Frequently asked questions
What is Feature stores?
Serving and governing ML features for training and inference. Jobs: offline feature compute; online feature serving; point-in-time correctness.
What should not be listed as Feature stores?
Products whose buyer job is data prep tools, data modelling suites, or vector databases. Those belong on their own category page so search queries are not split.
Has AI Trustmark independently assessed every Feature stores supplier?
No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.
What are Feature stores?
Serving and governing ML features for training and inference. Jobs: offline feature compute; online feature serving; point-in-time correctness.
What model or provider changes should a buyer insist on being told about?
Material change usually includes a new model family, new region, new subprocessor, new write-capable tool, or a change that affects logging, privacy or human oversight. Those changes should trigger evidence refresh rather than a silent release.
How should buyers verify where AI customer data is processed?
Ask for the named processing locations, cloud regions and any subprocessors that see prompts, files or outputs. A directory listing is not evidence of residency. Independent assessment records the locations that were in scope on the assessment date.
Does a TrustMark on one product cover the rest of the company?
No. Independent assessment is scoped to the named organisation and, where relevant, the named product. Category pages list suppliers as a topic label. They do not imply that every listed company has been assessed.
What incident-handling evidence is useful for AI suppliers?
Buyers should see how AI-specific failures are detected, contained and notified — including unsafe outputs, data leakage and unauthorised agent actions. An incident policy that never mentions models, prompts or tools is incomplete for this class of product.