--- title: "llm-app vs spiceai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pathwaycom-llm-app-vs-spiceai-spiceai" tools: ["pathwaycom-llm-app", "spiceai-spiceai"] --- # llm-app vs spiceai *GraphCanon updated Aug 24, 2026* ## Verdict Pick llm-app if llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz; pick spiceai if spiceAI is designed for real-time analytics and operates in Rust to integrate seamlessly with operational databases. [llm-app](https://pathway.com/developers/templates/) reports 59k GitHub stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. [spiceai](https://docs.spiceai.org) has 3.1k stars, 222 forks, and 662 open issues, last pushed Aug 24, 2026. Figures are from public GitHub metadata via [llm-app's repository](https://github.com/pathwaycom/llm-app) and [spiceai's repository](https://github.com/spiceai/spiceai). | | [llm-app](/tools/pathwaycom-llm-app.md) | [spiceai](/tools/spiceai-spiceai.md) | | --- | --- | --- | | Tagline | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | A real-time analytics node for data-grounded AI applications | | Stars | 59,037 | 3,069 | | Forks | 1,466 | 222 | | Open issues | 8 | 662 | | Language | Jupyter Notebook | Rust | | Adopt for | llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz | SpiceAI is designed for real-time analytics and operates in Rust to integrate seamlessly with operational databases. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, LLM Frameworks, Vector Databases | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-app](/tools/pathwaycom-llm-app.md) | [spiceai](/tools/spiceai-spiceai.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 41d | 0d | | Open issues (now) | 8 | 662 | | Stars delta | +11 (30d) | +22 (30d) | | Open issues delta | -2 (30d) | +238 (30d) | | Full report | [trust report](/tools/pathwaycom-llm-app/trust.md) | [trust report](/tools/spiceai-spiceai/trust.md) | ## Decision facts: llm-app - **Requirements:** Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others. - **Adopt for:** llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz ## Decision facts: spiceai - **Adopt for:** SpiceAI is designed for real-time analytics and operates in Rust to integrate seamlessly with operational databases. ## Choose when ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; spiceai is Rust. - License: llm-app is MIT, spiceai is Apache-2.0. - Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.. - Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation. - Also covers Vector Databases. - - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ### Choose spiceai if… - spiceai is primarily Rust; llm-app is Jupyter Notebook. - License: spiceai is Apache-2.0, llm-app is MIT. - Tags unique to spiceai: accelerated sql, llm-inference, operational database integration, real-time analytics. - spiceai ships Docker support for self-hosted deployment. - When you need real-time data-grounded AI applications that require fast SQL query execution, search capabilities, or LLM-inference ## When NOT to use llm-app - - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ## When NOT to use spiceai - If your project already has a robust solution for real-time analytics that does not benefit from being rewritten in Rust - Where the ecosystem preference is not Rust, as SpiceAI's accelerated query engine and integration features are tied closely with Rust ## Common questions ### What is the difference between llm-app and spiceai? llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. spiceai: A real-time analytics node for data-grounded AI applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-app over spiceai? Choose llm-app over spiceai when llm-app is primarily Jupyter Notebook; spiceai is Rust; License: llm-app is MIT, spiceai is Apache-2.0; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ### When should I choose spiceai over llm-app? Choose spiceai over llm-app when spiceai is primarily Rust; llm-app is Jupyter Notebook; License: spiceai is Apache-2.0, llm-app is MIT; Tags unique to spiceai: accelerated sql, llm-inference, operational database integration, real-time analytics; spiceai ships Docker support for self-hosted deployment; When you need real-time data-grounded AI applications that require fast SQL query execution, search capabilities, or LLM-inference. ### When should I avoid llm-app? - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ### When should I avoid spiceai? If your project already has a robust solution for real-time analytics that does not benefit from being rewritten in Rust Where the ecosystem preference is not Rust, as SpiceAI's accelerated query engine and integration features are tied closely with Rust ### Is llm-app or spiceai more popular on GitHub? llm-app has more GitHub stars (59,037 vs 3,069). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-app and spiceai open source? Yes - both are open-source projects on GitHub (llm-app: MIT, spiceai: Apache-2.0). ### Where can I find alternatives to llm-app or spiceai? GraphCanon lists graph-backed alternatives at [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) and [spiceai alternatives](/tools/spiceai-spiceai/alternatives) ([llm-app markdown twin](/tools/pathwaycom-llm-app/alternatives.md), [spiceai markdown twin](/tools/spiceai-spiceai/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-spiceai-spiceai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-app or spiceai? llm-app: Steady. spiceai: Very active. 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 spiceai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-app trust report](/tools/pathwaycom-llm-app/trust); [spiceai trust report](/tools/spiceai-spiceai/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/_