What are the primary features of the Kylin system?

The main function of the Kylin system is to provide high-performance, low-latency online analytical processing (OLAP) capabilities in the field of big data analysis. It is designed to perform queries and analysis on large-scale data sets using multidimensional data models, supporting complex multidimensional analysis queries such as slicing, dicing, and drilling. Its key features include:

1. Based on column storage engine: Kylin system utilizes a column-based data model to efficiently handle large datasets.
2. Build multi-dimensional data models: Kylin system has the ability to create multi-dimensional data models, converting large-scale datasets into multi-dimensional models to support complex multi-dimensional analysis queries.
3. High-performance query engine: The Kylin system utilizes the Cube computation engine to rapidly respond to complex multidimensional queries, offering low-latency online analytical capabilities.
4. Support for SQL queries: Kylin system is compatible with standard SQL query language, allowing users to perform queries and analysis using familiar SQL syntax.
5. Support real-time data updates: The Kylin system allows for real-time data updates and incremental building, meeting the needs of real-time data analysis.
6. Scalability and fault-tolerance: The Kylin system has excellent scalability and fault-tolerance, which enables it to handle large-scale data sets and high volumes of concurrent query requests.

In conclusion, the main function of the Kylin system is to provide high performance, low latency online analysis capabilities, support complex multi-dimensional analysis queries, and have good scalability and fault tolerance.