---
title: "llm-app vs raglite"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/pathwaycom-llm-app-vs-superlinear-ai-raglite"
tools: ["pathwaycom-llm-app", "superlinear-ai-raglite"]
---

# llm-app vs raglite

*GraphCanon updated Sep 20, 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 raglite if rAGLite offers specialized capabilities for integrating Retrieval-Augmented Generation (RAG) models with DuckDB or PostgreSQL.

[llm-app](https://pathway.com/developers/templates/) reports 59k GitHub stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. [raglite](https://github.com/superlinear-ai/raglite) has 1.2k stars, 109 forks, and 14 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [llm-app's repository](https://github.com/pathwaycom/llm-app) and [raglite's repository](https://github.com/superlinear-ai/raglite).

| | [llm-app](/tools/pathwaycom-llm-app.md) | [raglite](/tools/superlinear-ai-raglite.md) |
| --- | --- | --- |
| Tagline | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL |
| Stars | 58,920 | 1,202 |
| Forks | 1,498 | 109 |
| Open issues | 8 | 14 |
| Language | Jupyter Notebook | Python |
| 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. | RAGLite offers specialized capabilities for integrating Retrieval-Augmented Generation (RAG) models with DuckDB or PostgreSQL. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT License | MPL-2.0 |
| Categories | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | Data & Retrieval, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [llm-app](/tools/pathwaycom-llm-app.md) | [raglite](/tools/superlinear-ai-raglite.md) |
| --- | --- | --- |
| Days since push | 74d | 33d |
| Open issues (now) | 8 | 14 |
| Stars delta | -117 (30d) | +6 (30d) |
| Open issues delta | 0 (30d) | +1 (30d) |
| Full report | [trust report](/tools/pathwaycom-llm-app/trust.md) | [trust report](/tools/superlinear-ai-raglite/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: raglite

- **Adopt for:** RAGLite offers specialized capabilities for integrating Retrieval-Augmented Generation (RAG) models with DuckDB or PostgreSQL.

## Choose when

### Choose llm-app if…

- llm-app is primarily Jupyter Notebook; raglite is Python.
- License: llm-app is MIT, raglite is MPL-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.
- Also covers Evaluation & Observability, Inference & Serving.
- 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 raglite if…

- raglite is primarily Python; llm-app is Jupyter Notebook.
- License: raglite is MPL-2.0, llm-app is MIT.
- Tags unique to raglite: chainlit, colbert, duckdb, evals.
- raglite ships Docker support for self-hosted deployment.
- - You need to leverage Retriever-Reader architectures specifically optimized for either DuckDB or PostgreSQL backend databases.

## 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 raglite

- - The project demands integration with RAG systems that natively support database backends other than DuckDB and PostgreSQL, as RAGLite is limited to these two options.
- - You are looking for a more generalized framework that supports multiple vector search engines besides those compatible with DuckDB or PostgreSQL.

## Common questions

### What is the difference between llm-app and raglite?

llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. raglite: Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL. See the comparison table for live GitHub stats and shared categories.

### When should I choose llm-app over raglite?

Choose llm-app over raglite when llm-app is primarily Jupyter Notebook; raglite is Python; License: llm-app is MIT, raglite is MPL-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; Also covers Evaluation & Observability, Inference & Serving; 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 raglite over llm-app?

Choose raglite over llm-app when raglite is primarily Python; llm-app is Jupyter Notebook; License: raglite is MPL-2.0, llm-app is MIT; Tags unique to raglite: chainlit, colbert, duckdb, evals; raglite ships Docker support for self-hosted deployment; - You need to leverage Retriever-Reader architectures specifically optimized for either DuckDB or PostgreSQL backend databases.

### 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 raglite?

- The project demands integration with RAG systems that natively support database backends other than DuckDB and PostgreSQL, as RAGLite is limited to these two options. - You are looking for a more generalized framework that supports multiple vector search engines besides those compatible with DuckDB or PostgreSQL.

### Is llm-app or raglite more popular on GitHub?

llm-app has more GitHub stars (58,920 vs 1,202). Stars measure visibility, not whether either tool fits your constraints.

### Are llm-app and raglite open source?

Yes - both are open-source projects on GitHub (llm-app: MIT, raglite: MPL-2.0).

### Where can I find alternatives to llm-app or raglite?

GraphCanon lists graph-backed alternatives at [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) and [raglite alternatives](/tools/superlinear-ai-raglite/alternatives) ([llm-app markdown twin](/tools/pathwaycom-llm-app/alternatives.md), [raglite markdown twin](/tools/superlinear-ai-raglite/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-superlinear-ai-raglite.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, llm-app or raglite?

llm-app: Steady. raglite: 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 llm-app and raglite?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-app trust report](/tools/pathwaycom-llm-app/trust); [raglite trust report](/tools/superlinear-ai-raglite/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/_