Qwak
MLOps Platforms
ML engineering platform for building, training, and deploying models with integrated feature store and serving.
Unified model management and collaborationOne click model training and fine tuningScalable model deployment
Alternatives to Hopsworks
- 1Feature Stores, MLOps Platforms
- 2Feature Stores, MLOps Platforms
Layer
AI Data Pipeline
Collaborative ML platform for building and sharing feature engineering and model training pipelines.
Free trialSOC 2Usage-basedData Pipeline OrchestrationFeature Stores - 3Feature Stores, Machine Learning Platforms
Zipline
Feature Stores
Feature store platform for ML engineers to simplify data retrieval for machine learning.
Free planMachine Learning PlatformsAI Infrastructure - 4Feature Stores, MLOps Platforms
Feast
Feature Stores
Open-source feature store for ML serving production features to models with offline and online storage.
Free planData QualityMLOps Platforms - 5Feature Stores, MLOps Platforms
Featureform
Feature Stores
Virtual feature store layering on top of existing infrastructure for managing ML features without migration.
Free planMLOps PlatformsAI/ML Infrastructure - 6Feature Stores
Kaskada
Feature Stores
Feature engineering platform acquired by DataStax for real-time machine learning features.
- 7Feature Stores, MLOps Platforms
Iguazio
MLOps Platforms
MLOps platform for deploying and managing ML models in production with real-time data processing and feature store.
Free trialFeature Stores - 8Feature Stores, MLOps Platforms
Tecton
Feature Stores
Enterprise feature platform for managing and serving ML features in production with real-time data pipelines.
SOC 2ISO 27001GDPRUsage-basedMLOps PlatformsAI/ML InfrastructurePriceUsage-based
- 9Feature Stores
Scribble Data
Feature Stores
Enterprise AI applications platform for data teams building feature stores and production decision systems.
Feature engineering and managementData lineage and traceabilityPolicy based execution and governance - 10MLOps Platforms
Valohai
MLOps Platforms
MLOps platform for automating model training, evaluation, and deployment with version control and pipeline orchestration.
Experiment tracking and versioningDistributed model trainingMulti cloud and on premises deployment
