Jinmu Case Study on Couchbase Implementation

This case study details Jinmu Information's implementation of Couchbase for its AI Assistant project, aimed at enhancing real-time audio and video solutions. Jinmu, a professional IT data consulting provider, required a document-based NoSQL database that could deliver a consistent and highly available key-value store. The study outlines the challenges faced by Jinmu, including the need for high concurrency query support and advanced features such as vector search capabilities and SQL syntax support. The outcomes of using Couchbase included improved application performance and stability, with the ability to handle 70 million documents and 8,000 operations per second at 10ms response times. The AI Assistant application leverages Couchbase to capture, organize, and summarize conversations, providing timely notifications and contextually accurate responses. The case study concludes with Jinmu's plans to further integrate time series data and LLM capabilities into the application, showcasing the flexibility and efficiency of Couchbase in modern application development.