Alternatives to Amazon SageMaker Feature Store

Feast

Feast suits data scientists, MLOps engineers, data engineers, and AI engineers managing features for model training and inference.

Hopsworks Feature Store

Hopsworks suits data scientists, data engineers, developers, platform and security engineers, and administrators building production AI systems.

Databricks Feature Store

It suits teams building AI or machine-learning models that need governed feature registration, lineage and serving.

Feathr suits teams that build machine-learning features across batch, streaming, or online workflows and need a shared registry.

JFrog ML is presented for data scientists, ML engineers and AI developers taking AI and machine-learning services into production.

It suits teams building machine-learning feature workflows with SQL who need online and batch processing or a self-hosted deployment.

Agent Platform Feature Store

It suits teams managing BigQuery-based machine-learning features for online predictions and monitored pipelines.

It is intended for data science and machine learning teams.

Metarank suits teams building personalized search, recommendations, or learning-to-rank into their systems.

Chalk

Chalk suits data engineering, MLOps, AI/ML, data science, and AI platform teams building or operating models and agents.

This Feature Store suits data scientists, AI engineers, developers, and IT operations teams using self-managed OpenShift AI.

Vertex AI Vector Search

It suits teams building semantic or hybrid search, recommendation, retrieval-augmented generation, chatbot, and multimodal applications on Google Cloud.

Snowflake Feature Store

It suits data-science and machine-learning teams already working in Snowflake who need governed feature creation, lineage, and serving.

It suits data-science teams that need shared feature data for training and inference.

Azure Machine Learning

Azure Machine Learning suits teams needing web-based forecasting, evaluation, automated learning or model deployment.