Distributed real-time database management system and implementation method applicable to electric system

A distributed real-time and management system technology, applied in the field of distributed real-time databases, can solve the problem that a single real-time database cannot meet actual needs, and achieve the effect of facilitating unified data planning, flexible configuration, and high module independence
CN103886104AInactive Publication Date: 2014-06-25CHINA REALTIME DATABASE
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA REALTIME DATABASE
Publication Date
2014-06-25
Estimated Expiration
Not applicable ยท inactive patent

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Abstract

The invention discloses a distributed real-time database management system and an implementation method applicable to an electric system and belongs to the field of database technologies. The real-time database management system comprises a server side, a real-time database side and a client side. The distributed management of real-time databases can be achieved through mechanisms such as file mapping, instance IDs, version numbers and client side caching. Through the distributed real-time database management system and the implementation method applicable to the electric system, transparency of multiple database instances is achieved, access of clients to the multiple database instances equals to access to a single database instance, the province-wide centralized deployment of the databases are facilitated, the province-wide unified data schema, data models and data standards are facilitated, and the access requirements of existing data and future data can be met.
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Description

technical field

[0001] The invention belongs to the field of distributed real-time databases, in particular to a distributed real-time database management method. Background technique

[0002] With the continuous deepening of industrialization and informatization "integration of industrialization and industrialization", industrial automation systems are facing increasing pressure to process massive data. Taking the power system as an example, with the continuous expansion of the scale of the power grid and the deepening of research and application of digital power grids and digital substations, the system faces more and more collection points. The collection volume of a medium-sized area can reach 20,000 to 100,000, and a large-scale survey may face a data collection scale of 200,000 to 1 million in the future, and the data center can reach 5 million to 10 million or even tens of millions of data collection scale.

[0003] The single database management method currently us...

Claims

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