YMatrix is an enterprise-grade distributed database product based on the PostgreSQL system. YMatrix integrates time series, analysis (OLAP), transactions (OLTP), and AI capabilities into one, offering core advantages such as full coverage, low cost, high performance, high availability, easy scalability, and security compliance. It uses the concept of “hyper-convergence” to solve the problems of complex traditional architecture and high operation and maintenance costs, providing enterprises with a “one-stop” data storage solution.
Specializes in time series scenarios, providing powerful high concurrency capabilities and deep optimization for time series scenarios such as intelligent connected vehicles and smart factories. Supports advanced syntax such as CTE and window functions, as well as native time series-specific functions. Specifically supports out-of-order and batch writing for complex network environments. Supports zero service interruption cluster horizontal expansion to flexibly respond to data growth. Supports downgrading cold data to object storage, which can significantly reduce storage costs.
Supports massive data volumes ranging from TB to PB, providing reliable and high-performance data processing and data service capabilities for large-scale enterprise reporting, BI, and other analytical applications. Not only does it offer powerful performance and excellent multi-table JOIN capabilities, but it also supports advanced analytical features such as window functions and materialized views. In addition to traditional data warehouse batch processing capabilities, it features the innovative Domino stream computing engine, enabling real-time stream processing of data via SQL to replace Flink and Spark.
Complete ACID properties provide financial-grade data reliability, meeting the requirements of important systems such as finance and ERP for database performance, data accuracy, and consistency. It also supports advanced features such as stored procedures, triggers, and off-site disaster recovery, making it widely applicable to various complex transaction scenarios.
It provides vector search capabilities for large language models (LLMs), helping enterprises quickly build “AI agents” based on business data; without the need for Spark, PL/Python can be executed directly within the database, fully utilizing hardware resources and improving machine learning efficiency; it also supports multi-modal data management and hybrid search capabilities.
SQL : 2016 standardMatrixUI is a graphical operation and maintenance management tool designed to provide operation and maintenance engineers with a simple, easy-to-use, and comprehensive information source.
MatrixGate is a high-performance data loading tool that distributes data evenly across all data nodes to achieve parallel writing
MatrixArchive is to save all data saved by a normally running YMatrix database cluster at a specific point in time and backup data according to certain rules. Backed up data can ensure data integrity and consistency at that specific point in time. In addition, from all files for a given backup, an available YMatrix database cluster can be restored, with the content consistent with the data from the original cluster at a specific point in time.
MatrixShift is a dedicated data migration tool that supports full, incremental, and conditional migration from various versions of Greenplum and YMatrix. It has the characteristics of efficient (point-to-point transmission, small table optimization, transmission compression), flexible configuration, etc.
YMatrix System Architecture Quick Installation Standard Cluster Deployment Solution Scenario Application
In addition to providing [Enterprise Version] (https://ymatrix.cn/download), YMatrix also provides a free trial of [Community Version] (https://ymatrix.cn/download). Welcome your use and experience!