The hybrid search feature in Microsoft Azure Cosmos DB has added significant value to my AI and search workloads, with response times that are much faster and far better than querying SQL databases, resulting in very low response times.
Microsoft Azure Cosmos DB, known for its scalability and automatic features, manages large-scale operations across various data models, offering high performance for real-time analytics. Though integration with Microsoft services aids usability, users face challenges with its complex pricing and slow technical support. The system's API, especially for MongoDB, needs enhancement, and documentation for migrations remains a hurdle. Improvements in auto-scaling architecture would further optimize user experience and operational costs.
