Starwhale

Overview

Starwhale is an MLOps/LLMOps platform for managing machine learning workflows. It provides tools for dataset versioning, model evaluation, and experiment tracking. The platform is built in Java and is available as a community-driven open source project.

Best for

Best for
Teams seeking an open source MLOps platform that can handle both traditional ML and LLM workflows

Use cases

• Versioning and managing ML datasets across experiments
• Evaluating and comparing model performance in a structured pipeline
• Tracking and reproducing machine learning experiments

Notes

Starwhale is an MLOps/LLMOps platform for managing machine learning workflows. It provides tools for dataset versioning, model evaluation, and experiment tracking. The platform is built in Java and is available as a community-driven open source project.

238 stars on GitHub. Last updated 2024-12-20. Licensed Apache-2.0.

Use cases

• Versioning and managing ML datasets across experiments
• Evaluating and comparing model performance in a structured pipeline
• Tracking and reproducing machine learning experiments

Pros

• Open source with no vendor lock-in
• Covers the full ML lifecycle from data to evaluation
• Supports both traditional ML and LLM workflows

Cons

• Small community with only 238 GitHub stars
• Java-based codebase may be less familiar to Python-centric ML teams
• Limited documentation and ecosystem compared to more mature platforms

Indexed from awesome-llmops and enriched against its public facts.