Hopsworks

The AI Lakehouse: Feature Store, Model Registry, Model Serving

Freemium

Description

Hopsworks is an advanced AI Lakehouse platform designed to unify data management and machine learning operations for enterprises. It empowers organizations to centralize, share, and reuse ML features at scale through its robust Feature Store, which is powered by the real-time AI database RonDB for sub-millisecond latency. The platform facilitates the orchestration and monitoring of end-to-end ML workflows, from data ingestion and feature engineering to model training and deployment, thereby streamlining the development of reliable AI systems.

Furthermore, Hopsworks delivers comprehensive MLOps management, including efficient GPU management to maximize utilization for demanding tasks such as training Large Language Models (LLMs) and Deep Learning models. It offers exceptional flexibility with deployment options across cloud providers (AWS, Azure, GCP), on-premises data centers, or hybrid setups, all managed via Kubernetes to ensure data sovereignty and security. By transforming existing data layers into a high-performance AI platform built on open standards, Hopsworks accelerates model development cycles, enhances operational efficiency, and improves governance for AI projects.

Key Features

AI Lakehouse: Unified platform for data and AI with real-time capabilities, supporting open table formats (Delta Lake, Apache Hudi, Apache Iceberg).
Feature Store: Centralize, share, and reuse ML features at scale, powered by RonDB for sub-millisecond latency and high feature freshness.
MLOps Management: Orchestrate, monitor, and govern end-to-end ML workflows, including reproducibility, testing, and lineage.
GPU Management: Maximize GPU utilization for LLMs and Deep Learning with dynamic allocation, multi-GPU training support (Ray/PyTorch), and real-time monitoring.
Model Registry: Track, version, and deploy models (KServe/vLLM) with full lineage integrated with the feature store.
Real-time Feature Serving: Delivers features with <1ms latency and <1sec feature freshness, powered by RonDB.
Feature and Data Versioning: Provides full feature version history with time travel capabilities and data versioning with Open Table Formats.
Vector Index: Integrated Vector Index within the Online Feature Store for efficient similarity search.
Sovereign AI Deployment: Supports deployment on any cloud (AWS, Azure, GCP), hybrid, on-premises, or air-gapped environments using Kubernetes.
Data Transformations for ML: Supports model-independent, model-dependent, and real-time transformations for preparing data for machine learning.

Use Cases

Generative AI development and deployment
Real-time Fraud Detection systems
Building Personalized LLM applications with private data
Developing Customer 360 platforms
Creating advanced Recommendation Systems (RecSys)
Powering Image Analysis pipelines
Implementing Predictive Analytics solutions

Frequently Asked Questions

What makes Hopsworks' real-time feature serving performant?

Hopsworks offers real-time feature serving with less than 1ms latency and sub-second feature freshness, which is powered by RonDB, its integrated, high-performance, real-time AI database.

Can Hopsworks be deployed in secure or isolated environments?

Yes, Hopsworks supports deployment on-premises, in hybrid setups, or even in air-gapped environments using Kubernetes, in addition to major cloud providers like AWS, Azure, and GCP. This ensures data sovereignty and accommodates various security requirements.

What kind of data transformations does Hopsworks support for machine learning?

Hopsworks supports a comprehensive set of data transformations for ML, including model-independent transformations, model-dependent transformations, and real-time transformations on historical or streaming data.

How does Hopsworks facilitate feature discovery within an organization?

Hopsworks provides robust feature discovery mechanisms including free-text search across features, a UI-based catalog for browsing available features and feature groups, and complete feature lineage to understand data origins and dependencies.

What open table formats are supported by Hopsworks' AI Lakehouse?

Hopsworks' AI Lakehouse supports popular open table formats such as Delta Lake, Apache Hudi, and Apache Iceberg. These can be used on S3 or HopsFS/S3, allowing users to leverage their existing data lake infrastructure.