--- title: "OpenMemory vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/caviraoss-openmemory-vs-pathwaycom-llm-app" tools: ["caviraoss-openmemory", "pathwaycom-llm-app"] --- # OpenMemory vs llm-app *GraphCanon updated Aug 21, 2026* ## Verdict Pick OpenMemory if openMemory offers local storage tailored for AI agents like Claude Desktop and GitHub Copilot; 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. [OpenMemory](https://openmemory.cavira.app) reports 4.5k GitHub stars, 501 forks, and 18 open issues, last pushed Aug 20, 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 [OpenMemory's repository](https://github.com/CaviraOSS/OpenMemory) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [OpenMemory](/tools/caviraoss-openmemory.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | Local persistent memory store for LLM applications | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 4,457 | 59,037 | | Forks | 501 | 1,466 | | Open issues | 18 | 8 | | Language | TypeScript | Jupyter Notebook | | Adopt for | OpenMemory offers local storage tailored for AI agents like Claude Desktop and GitHub Copilot. | 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 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [OpenMemory](/tools/caviraoss-openmemory.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 41d | | Open issues (now) | 18 | 8 | | Stars delta | +100 (30d) | +11 (30d) | | Open issues delta | +5 (30d) | -2 (30d) | | Full report | [trust report](/tools/caviraoss-openmemory/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: OpenMemory - **Adopt for:** OpenMemory offers local storage tailored for AI agents like Claude Desktop and GitHub Copilot. ## 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 ## Choose when ### Choose OpenMemory if… - OpenMemory is primarily TypeScript; llm-app is Jupyter Notebook. - License: OpenMemory is Apache-2.0, llm-app is MIT. - Tags unique to OpenMemory: ai-agents, embeddings, long-term-memory, memory-engine. - OpenMemory ships Docker support for self-hosted deployment. - Need to integrate persistent memory support for specific LLMs like Claude. ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; OpenMemory is TypeScript. - License: llm-app is MIT, OpenMemory 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 LLM Frameworks. - - 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 NOT to use OpenMemory - Require cloud-based memory storage services. - Your project must use languages other than TypeScript. - Seek a generic vector database without specific LLM integrations. ## 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. ## Common questions ### What is the difference between OpenMemory and llm-app? OpenMemory: Local persistent memory store for LLM 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 OpenMemory over llm-app? Choose OpenMemory over llm-app when OpenMemory is primarily TypeScript; llm-app is Jupyter Notebook; License: OpenMemory is Apache-2.0, llm-app is MIT; Tags unique to OpenMemory: ai-agents, embeddings, long-term-memory, memory-engine; OpenMemory ships Docker support for self-hosted deployment; Need to integrate persistent memory support for specific LLMs like Claude. ### When should I choose llm-app over OpenMemory? Choose llm-app over OpenMemory when llm-app is primarily Jupyter Notebook; OpenMemory is TypeScript; License: llm-app is MIT, OpenMemory 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 LLM Frameworks; - 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 avoid OpenMemory? Require cloud-based memory storage services. Your project must use languages other than TypeScript. Seek a generic vector database without specific LLM integrations. ### 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. ### Is OpenMemory or llm-app more popular on GitHub? llm-app has more GitHub stars (59,037 vs 4,457). Stars measure visibility, not whether either tool fits your constraints. ### Are OpenMemory and llm-app open source? Yes - both are open-source projects on GitHub (OpenMemory: Apache-2.0, llm-app: MIT). ### Where can I find alternatives to OpenMemory or llm-app? GraphCanon lists graph-backed alternatives at [OpenMemory alternatives](/tools/caviraoss-openmemory/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([OpenMemory markdown twin](/tools/caviraoss-openmemory/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/caviraoss-openmemory-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, OpenMemory or llm-app? OpenMemory: 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 OpenMemory and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [OpenMemory trust report](/tools/caviraoss-openmemory/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=caviraoss-openmemory`](/api/graphcanon/graph?tool=caviraoss-openmemory) - 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/_