--- title: "amazon-bedrock-samples vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aws-samples-amazon-bedrock-samples-vs-pathwaycom-llm-app" tools: ["aws-samples-amazon-bedrock-samples", "pathwaycom-llm-app"] --- # amazon-bedrock-samples vs llm-app *GraphCanon updated Jul 11, 2026* ## Verdict Pick amazon-bedrock-samples when license: amazon-bedrock-samples is MIT-0, llm-app is MIT; pick llm-app when license: llm-app is MIT, amazon-bedrock-samples is MIT-0. [amazon-bedrock-samples](https://aws.amazon.com/bedrock/) reports 1.5k GitHub stars, 701 forks, and 130 open issues, last pushed Jun 30, 2026. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.4k forks, and 10 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [amazon-bedrock-samples's repository](https://github.com/aws-samples/amazon-bedrock-samples) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 1,470 | 59,068 | | Forks | 701 | 1,432 | | Open issues | 130 | 10 | | Language | Jupyter Notebook | Jupyter Notebook | | 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 | | Persona | - | - | | Runtime | - | - | | License | MIT-0 | MIT | | Categories | LLM Frameworks, Vector Databases | LLM Frameworks, Vector Databases, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 11d | 5d | | Open issues (now) | 130 | 10 | | Full report | [trust report](/tools/aws-samples-amazon-bedrock-samples/trust.md) | [trust report](/tools/pathwaycom-llm-app/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 ## Choose when ### Choose amazon-bedrock-samples if… - License: amazon-bedrock-samples is MIT-0, llm-app is MIT. - Tags unique to amazon-bedrock-samples: embeddings, amazon-bedrock, amazon-titan, rag. ### Choose llm-app if… - License: llm-app is MIT, amazon-bedrock-samples is MIT-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: vector-database, llm, hugging-face, retrieval-augmented-generation. - Also covers Data & Retrieval. - - 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 amazon-bedrock-samples - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## 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 amazon-bedrock-samples and llm-app? amazon-bedrock-samples: This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models. 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 amazon-bedrock-samples over llm-app? Choose amazon-bedrock-samples over llm-app when License: amazon-bedrock-samples is MIT-0, llm-app is MIT; Tags unique to amazon-bedrock-samples: embeddings, amazon-bedrock, amazon-titan, rag. ### When should I choose llm-app over amazon-bedrock-samples? Choose llm-app over amazon-bedrock-samples when License: llm-app is MIT, amazon-bedrock-samples is MIT-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: vector-database, llm, hugging-face, retrieval-augmented-generation; Also covers Data & Retrieval; - 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 amazon-bedrock-samples? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### 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 amazon-bedrock-samples or llm-app more popular on GitHub? llm-app has more GitHub stars (59,068 vs 1,470). Stars measure visibility, not whether either tool fits your constraints. ### Are amazon-bedrock-samples and llm-app open source? Yes - both are open-source projects on GitHub (amazon-bedrock-samples: MIT-0, llm-app: MIT). ### Where can I find alternatives to amazon-bedrock-samples or llm-app? GraphCanon lists graph-backed alternatives at [amazon-bedrock-samples alternatives](/tools/aws-samples-amazon-bedrock-samples/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([amazon-bedrock-samples markdown twin](/tools/aws-samples-amazon-bedrock-samples/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/aws-samples-amazon-bedrock-samples-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, amazon-bedrock-samples or llm-app? amazon-bedrock-samples: Active. llm-app: 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 amazon-bedrock-samples and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [amazon-bedrock-samples trust report](/tools/aws-samples-amazon-bedrock-samples/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples`](/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples) - 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/_