Analytical databases are designed for high-performance read operations that scale effectively to handle large datasets, making them suitable for tasks such as data mining, predictive analysis, and business intelligence. They offer various features like columnar data storage, in-memory processing, parallel processing, data aggregation and transformation, horizontal scalability, and advanced query capabilities. These databases are ideal for handling complex queries and provide fast access to large sets of data, enabling real-time insights and faster decision-making processes. They can be categorized into different types such as column-oriented databases, data warehouses, OLAP, and time series databases, each with its unique architecture and data model. Analytical databases have numerous use cases, including financial markets historical data analysis, user behavioral data collection and analysis, historical sensor data, real-time security and fraud analysis, and natural language processing data.