dingo vs PaddleOCR
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| dingo | PaddleOCR | |
|---|---|---|
| Tagline | Multi-modal vector database supporting unified SQL access to structured and unstructured data | PaddleOCR: A powerful OCR toolkit for transforming PDFs/images into structured data |
| Stars | 1.7k | 85k |
| Forks | 264 | 11k |
| Open issues | 8 | 221 |
| Language | Java | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | May 25, 2026 | Jun 26, 2026 |
| Categories | Vector Databases, Data & Retrieval | Data & Retrieval |
dingo
DingoDB is a high-concurrency, low-latency multi-modal vector database that supports both structured and unstructured data through MySQL-compatible SQL queries. It emphasizes horizontal scalability, data availability without external components, automatic sharding, hybrid scalar-vector retrieval, real-time index optimization, and tiered dataset handling for efficient management of large-scale datasets.
PaddleOCR
A lightweight OCR toolkit that converts images/PDF documents into LLM-friendly structured data formats like JSON or Markdown, supporting over 100 languages. Features include document parsing with vision-language models and multilingual text recognition.