deeplake vs llm-app
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| deeplake | llm-app | |
|---|---|---|
| Tagline | Deeplake: AI Data Runtime for Agents | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. |
| Stars | 9.2k | 59k |
| Forks | 721 | 1.4k |
| Open issues | 69 | 10 |
| Language | C++ | Jupyter Notebook |
| License | Apache-2.0 | MIT |
| Last pushed | May 21, 2026 | Jul 5, 2026 |
| Categories | Data & Retrieval, Model Training, Vector Databases | Data & Retrieval, LLM Frameworks |
deeplake
Deeplake is a scalable data management system optimized for deep learning applications, offering serverless PostgreSQL integration, multimodal support, and vector search capabilities, making it suitable for large language model-based projects.
C++
llm-app
Pathway Live Data Framework AI Pipelines provides LLM App Templates for deploying high-accuracy retrieval-augmented generation (RAG) and enterprise search applications. The templates sync with various data sources including file systems, Google Drive, Sharepoint, S3, Kafka, PostgreSQL, real-time APIs.
Jupyter Notebook