--- title: "llm-app vs starwhale" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pathwaycom-llm-app-vs-star-whale-starwhale" tools: ["pathwaycom-llm-app", "star-whale-starwhale"] --- # llm-app vs starwhale *GraphCanon updated Sep 29, 2026* ## Verdict Pick llm-app if llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs; pick starwhale if starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. [llm-app](https://pathway.com/developers/templates/) reports 59k GitHub stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. [starwhale](https://starwhale.ai) has 236 stars, 37 forks, and 120 open issues, last pushed Dec 20, 2024. Figures are from public GitHub metadata via [llm-app's repository](https://github.com/pathwaycom/llm-app) and [starwhale's repository](https://github.com/star-whale/starwhale). | | [llm-app](/tools/pathwaycom-llm-app.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Tagline | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | an MLOps/LLMOps platform | | Stars | 58,920 | 236 | | Forks | 1,498 | 37 | | Open issues | 8 | 120 | | Language | Jupyter Notebook | Java | | Adopt for | llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. | Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. | | Persona | - | - | | Runtime | - | - | | License | MIT License | Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. | | Categories | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-app](/tools/pathwaycom-llm-app.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 74d | 648d | | Open issues (now) | 8 | 120 | | Stars delta | -117 (30d) | -1 (30d) | | Full report | [trust report](/tools/pathwaycom-llm-app/trust.md) | [trust report](/tools/star-whale-starwhale/trust.md) | ## Decision facts: llm-app - **Pricing:** freemium - The repository is open-source under the MIT License, but additional services or support might incur costs. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **Adopt for:** llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **License detail:** MIT License ## Decision facts: starwhale - **Requirements:** Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments. - **Adopt for:** Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. - **License detail:** Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. ## Choose when ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; starwhale is Java. - License: llm-app is MIT, starwhale is Apache-2.0. - Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.. - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.. - Tags unique to llm-app: chatbot, hugging-face, llm-local, llm-prompting. - When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti ### Choose starwhale if… - starwhale is primarily Java; llm-app is Jupyter Notebook. - License: starwhale is Apache-2.0, llm-app is MIT. - Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.. - Tags unique to starwhale: ai, cloud-native, dataset, datastore. - Also covers LLM Frameworks. - When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ## When NOT to use llm-app - Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. - Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ## When NOT to use starwhale - In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. - For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ## Common questions ### What is the difference between llm-app and starwhale? llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. starwhale: an MLOps/LLMOps platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-app over starwhale? Choose llm-app over starwhale when llm-app is primarily Jupyter Notebook; starwhale is Java; License: llm-app is MIT, starwhale is Apache-2.0; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm-local, llm-prompting; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti. ### When should I choose starwhale over llm-app? Choose starwhale over llm-app when starwhale is primarily Java; llm-app is Jupyter Notebook; License: starwhale is Apache-2.0, llm-app is MIT; Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.; Tags unique to starwhale: ai, cloud-native, dataset, datastore; Also covers LLM Frameworks; When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ### When should I avoid llm-app? Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ### When should I avoid starwhale? In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ### Is llm-app or starwhale more popular on GitHub? llm-app has more GitHub stars (58,920 vs 236). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-app and starwhale open source? Yes - both are open-source projects on GitHub (llm-app: MIT, starwhale: Apache-2.0). ### Where can I find alternatives to llm-app or starwhale? GraphCanon lists graph-backed alternatives at [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) and [starwhale alternatives](/tools/star-whale-starwhale/alternatives) ([llm-app markdown twin](/tools/pathwaycom-llm-app/alternatives.md), [starwhale markdown twin](/tools/star-whale-starwhale/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/pathwaycom-llm-app-vs-star-whale-starwhale.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-app or starwhale? llm-app: Steady. starwhale: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for llm-app and starwhale? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-app trust report](/tools/pathwaycom-llm-app/trust); [starwhale trust report](/tools/star-whale-starwhale/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pathwaycom-llm-app`](/api/graphcanon/graph?tool=pathwaycom-llm-app) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_