--- title: "service-fabric vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-service-fabric-vs-pathwaycom-llm-app" tools: ["microsoft-service-fabric", "pathwaycom-llm-app"] --- # service-fabric vs llm-app *GraphCanon updated Sep 20, 2026* ## Verdict Pick service-fabric if service Fabric is an infrastructure platform for managing scalable and distributed microservices and stateful applications in cloud environments with C++ support; 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. [service-fabric](https://docs.microsoft.com/en-us/azure/service-fabric/) reports 3.1k GitHub stars, 401 forks, and 847 open issues, last pushed Sep 17, 2026. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [service-fabric's repository](https://github.com/microsoft/service-fabric) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [service-fabric](/tools/microsoft-service-fabric.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | A distributed systems platform for managing cloud-native microservices and stateful applications. | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | | Stars | 3,065 | 58,920 | | Forks | 401 | 1,498 | | Open issues | 847 | 8 | | Language | C++ | Jupyter Notebook | | Adopt for | Service Fabric is an infrastructure platform for managing scalable and distributed microservices and stateful applications in cloud environments with C++ support. | 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. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT License | | Categories | Inference & Serving, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [service-fabric](/tools/microsoft-service-fabric.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 1d | 74d | | Open issues (now) | 847 | 8 | | Stars delta | +4 (30d) | -117 (30d) | | Open issues delta | +2 (30d) | 0 (30d) | | Full report | [trust report](/tools/microsoft-service-fabric/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: service-fabric - **Requirements:** Min 32 GB RAM; Requires Docker - **Adopt for:** Service Fabric is an infrastructure platform for managing scalable and distributed microservices and stateful applications in cloud environments with C++ support. ## 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 ## Choose when ### Choose service-fabric if… - service-fabric is primarily C++; llm-app is Jupyter Notebook. - Requirements: Min 32 GB RAM; Requires Docker. - Tags unique to service-fabric: cloud-computing, cloud-native, containers, distributed-systems. - When you need to deploy and manage containerized services that are both stateless and stateful, leveraging advanced features of a robust distributed systems platform ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; service-fabric is C++. - 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, llm-local. - Also covers Data & Retrieval, Evaluation & Observability. - 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 NOT to use service-fabric - When building small applications that can be managed using simpler deployment tools, as Service Fabric may introduce unnecessary complexity and require more powerful hardware - If preferred development language is not C++ since integration support focuses heavily on this programming language, leading to potentially less streamlined operations for other languages ## 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. ## Common questions ### What is the difference between service-fabric and llm-app? service-fabric: A distributed systems platform for managing cloud-native microservices and stateful applications.. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories. ### When should I choose service-fabric over llm-app? Choose service-fabric over llm-app when service-fabric is primarily C++; llm-app is Jupyter Notebook; Requirements: Min 32 GB RAM; Requires Docker; Tags unique to service-fabric: cloud-computing, cloud-native, containers, distributed-systems; When you need to deploy and manage containerized services that are both stateless and stateful, leveraging advanced features of a robust distributed systems platform. ### When should I choose llm-app over service-fabric? Choose llm-app over service-fabric when llm-app is primarily Jupyter Notebook; service-fabric is C++; 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, llm-local; Also covers Data & Retrieval, Evaluation & Observability; 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 avoid service-fabric? When building small applications that can be managed using simpler deployment tools, as Service Fabric may introduce unnecessary complexity and require more powerful hardware If preferred development language is not C++ since integration support focuses heavily on this programming language, leading to potentially less streamlined operations for other languages ### 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. ### Is service-fabric or llm-app more popular on GitHub? llm-app has more GitHub stars (58,920 vs 3,065). Stars measure visibility, not whether either tool fits your constraints. ### Are service-fabric and llm-app open source? Yes - both are open-source projects on GitHub (service-fabric: MIT, llm-app: MIT). ### Where can I find alternatives to service-fabric or llm-app? GraphCanon lists graph-backed alternatives at [service-fabric alternatives](/tools/microsoft-service-fabric/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([service-fabric markdown twin](/tools/microsoft-service-fabric/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/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/microsoft-service-fabric-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, service-fabric or llm-app? service-fabric: Very active. llm-app: Steady. 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 service-fabric and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [service-fabric trust report](/tools/microsoft-service-fabric/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-service-fabric`](/api/graphcanon/graph?tool=microsoft-service-fabric) - 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/_