Bruinen Delta is a distributed SQLite database designed for edge computing, enabling local data storage and synchronization across devices without relying on cloud connectivity. It eliminates the complexities of distributed communication, allowing devices to operate independently and maintain data integrity even during network disruptions.
Funding
Funding not disclosed
Founders
Product
Problem
Edge computing environments often face challenges in maintaining data consistency and synchronization across devices, especially when network connectivity is intermittent or unreliable. Traditional solutions require complex distributed communication protocols, message queues, and retry mechanisms, adding significant engineering overhead.
Solution
Bruinen Delta is a distributed SQLite database designed specifically for edge computing, enabling local data storage and synchronization across devices without constant cloud connectivity. It simplifies edge AI/ML workflows by providing a familiar SQL interface on microcontrollers, phones, servers, and in the cloud. The database remains in sync across the network, ensuring devices continue to operate even when disconnected and automatically synchronizing changes upon reconnection. Bruinen Delta replaces complex distributed communication with a straightforward SQL database.
Target Audience
The primary target audience includes developers and organizations building edge computing solutions, particularly those involved in AI/ML, IoT, and other applications requiring local data processing and synchronization.
Features
- SQLite compatibility, providing a familiar database interface for web, embedded, server, and phone environments.
- Transport-agnostic operation, supporting various network types including WiFi, LAN, Bluetooth, LoRaWAN, and satellite.
- Conflict-free data replication using CRDTs (Conflict-Free Replicated Data Types) to enable data convergence even with diverging versions.
- Peer-to-peer network support, accommodating full peer-to-peer networks, gateways, and client/server models.
- Local data storage for fast read and write operations with minimal latency.
- Resilience to network disruptions, allowing devices to continue working offline and synchronize data upon reconnection.
- Enhanced security by enabling AI/ML workflows to operate on local data, reducing the transmission of sensitive information.