LadybugDB is an open‑source graph database that integrates native object storage into its core architecture, enabling efficient handling of large binary data alongside relational graph structures. By separating compute and storage, it allows independent scaling of query processing and data capacity, making it suitable for developers building data‑intensive applications such as media platforms, IoT services, and knowledge graphs.
Funding
Funding not disclosed
Founders
Product
Problem
Many modern applications require managing complex, interconnected data that includes large binary objects, yet most graph databases treat storage as an afterthought, leading to inefficient handling of object data and limited scalability.
Solution
LadybugDB addresses this gap by providing a graph database where object storage is integral to the core architecture. The platform separates compute and storage, allowing independent scaling of processing power and data capacity. By leveraging a modern, open‑source design, LadybugDB enables developers to store, query, and traverse rich graph structures that include large objects without sacrificing performance. The system’s flexible architecture supports seamless transition from prototype environments to production workloads, ensuring that applications can grow without re‑architecting their data layer.
Target Audience
Primary users are developers and engineering teams building data‑intensive applications—such as media platforms, IoT services, and knowledge graphs—that need scalable graph queries combined with robust object storage.
Features
- Native object storage embedded in the graph engine for efficient handling of binary data alongside relational nodes and edges
- Decoupled compute and storage layers that allow independent scaling of query processing and data capacity
- Open‑source codebase encouraging community contributions and transparent development
- Compatibility with standard graph query languages and APIs for easy integration into existing applications
- Modular architecture designed to move smoothly from development prototypes to enterprise‑grade deployments