Compare Dqlite vs. Novity

Dqlite is a high-speed, embedded SQL database that offers persistent storage and utilizes Raft consensus, making it an ideal choice for resilient IoT and Edge devices. Known as "distributed SQLite," Dqlite expands SQLite's capabilities across multiple machines, ensuring automatic failover and high availability to maintain application uptime. It employs C-Raft, an optimized implementation of Raft in C, which provides exceptional performance in transactional consensus and fault tolerance while maintaining SQLite’s renowned efficiency and compact size. C-Raft is specifically designed to reduce transaction latency, enabling faster operations. Both C-Raft and Dqlite are implemented in C, ensuring they are portable across various platforms. Released under the LGPLv3 license with a static linking exception, it guarantees broad compatibility. The system features a standard CLI pattern for initializing databases and managing the joining or leaving of voting members. It also incorporates minimal, configurable delays for failover alongside automatic leader election processes. Additionally, Dqlite supports a disk-backed database option with in-memory capabilities and adheres to SQLite's transaction protocols. The blend of these features makes Dqlite a powerful solution for modern data storage needs.

Novity’s TruPrognostics™ engine provides insights into the time remaining before maintenance is required, allowing you to visualize your plant's future and make informed choices in the present. Many organizations struggle with a lack of high-quality historical data, which hinders effective predictive analytics, but Novity addresses this issue using a unique blend of machine learning and physics-based models related to common machine faults. By integrating the appropriate IoT sensors, Novity ensures optimal performance regardless of the existing data quality. The application clearly indicates when equipment is likely to fail, minimizing the need for complex chart analysis and allowing you to focus on the efficient operation of your plant. This innovative approach leverages the principles of physics to deliver accurate predictions of failure timelines based on the specific progression of various faults. As a result, users can proactively manage maintenance schedules and enhance overall operational efficiency.