Jiangxi Electric Power Construction
High-performance Data Platform
Contact UsBusiness Background
Zhixin Energy Tech Co., a subsidiary of PowerChina Jiangxi Electric Power Construction, specializes in advanced energy technologies and digital power services.
As business scales up, the number of power plants and data volume have grown rapidly. To address this challenge, Zhixin Energy needs to build a high-performance, high-reliability data platform to realize real-time data collection, storage, computing and service-oriented management.
Business Challenges
Against the backdrop of rapidly expanding power station data scale, the original system faces severe tests regarding performance, cost, and security.
Double Pressure on Performance and Security
The data platform shall support real-time ingestion and processing of 4 million monitoring points per second. The original MySQL database cannot meet the high requirements of massive time-series data in terms of ingestion performance, storage scalability and computing efficiency.
High Storage Expence
Continuous massive time-series data leads to rapidly rising storage costs. The database requires efficient compression capability to significantly reduce storage and hardware expenses.
Insufficient Real-Time Data Processing
The original MySQL database cannot support stream computing, failing to deliver real-time analysis and response for power plant data.
Difficulties in Operations
The open-source database lacks dedicated graphical operational tools, increasing the difficulties in system maintenance and data management.
Demand for Compatiblity and Scalability
The database must be fully compatible with mainstream software and hardware environment, and support clustered deployment to ensure high availability and strong scalability.
KaiwuDB Solutions
High-Performance Data Ingestion
The multi-node KaiwuDB cluster breaks the performance bottlenecks of traditional MySQL in time-series data processing, achieving 300,000 rows per second write throughput and efficiently meeting the real-time data writing demand for 4 million monitoring points.Clustered Deployment for High Availability
A multi-replica database cluster is deployed, with the Raft consensus protocol ensuring data consistency. The system supports fault self-repairing and adaptive failover. Multi-node clustering delivers high availability and elastic scaling, ensuring stable long-term operation.Real-Time Stream Computing
KaiwuDB’s built-in stream computing engine aggregates power plant data in real time and conducts pipeline analysis, pushing results to BI dashboards. Lightweight deployment achieves big data analytics capabilities for different business scenarios, significantly improving data response efficiency.High Compression Storage
KaiwuDB supports online periodic data compression with configurable algorithms including gzip, lz4, lzo, Xz and zstd, achieving a storage compression ratio up to 1:10, greatly reducing storage costs.Visualized Operational Management
The data platform offers a graphical database management tool for database connection, database administration, schema management, and table management. It simplifies data governance, system monitoring and daily operations, effectively reducing operational complexity.
Client Benefits
Efficient Batch Data Management
Real-time data from 10 power plants has been efficiently integrated into the platform, with a total data volume of 1TB, laying a solid foundation for subsequent large-scale data input. High-compression-ratio storage has significantly reduced hardware resource investment by 32%.
Reliability and Scalability Guaranteed
Clustered deployment of KaiwuDB ensures high availability and scalability of the platform to meet the needs of continuously developing business. Our database technology is safe and controllable, significantly improving data security.
Real-Time Analysis Enhanced
KaiwuDB's stream computing technique enables real-time data processing and analysis, supporting high-speed query volumes (with a high maximum number of connections). In addition, KaiwuDB can process complex SQL, enabling real-time monitoring and intelligent evaluation of power plant operation status.
Operations Simplified
Graphical and visualized tools improve the efficiency of data management and operations, enhancing system maintainability and operational convenience.