With the explosion of demand for the Internet of Things, real-time databases are suddenly popular. In recent years, big Internet enterprises such as Alibaba, Tencent and Baidu have launched real-time database on the Internet of Things platform, which has become the core products to support their development in manufacturing, transportation, energy, smart city and other industrial fields for all kinds of partners in the industrial chain. This is an important signal that the industrial Internet of Things will explode.
As we all know, real-time database is an extremely important component service in the era of Internet of Things. Because the traditional spatial database has the performance bottleneck in the face of massive data, and the support ability for the joint application of time and space is limited. Based on its advantages in real-time data capability, real-time database expands spatial data capability, providing high-performance spatio-temporal data storage, time/space query, spatio-temporal analysis and mining capabilities, realizing the perfect integration of time and space, and facilitating the rapid development of GIS, spatio-temporal big data, Internet of Things +, industrial Internet and other industries.
What is a real-time database?
Real-time data is a series of data based on time. By connecting these data points in time coordinates, a multi-latitude report can be made in the past to reveal its trend, regularity and anomaly. Looking to the future, we can do big data analysis, machine learning, prediction and early warning. Simply put, it is a time - based database. In contrast to traditional databases, which only record the current value of data, real-time databases record all historical data.
Therefore, any scenario that needs to show its historical trend, cycle rule and anomaly, and further predict and analyze the future, is where the real-time database will play its role. In the era of the Internet of Things, industrial Internet, intelligent manufacturing, unmanned driving, equipment condition monitoring and many other scenarios need real-time and sustainable data as support. For example, in a smart factory enterprise, each factory has 20,000 monitoring points, a collection cycle of 500 milliseconds, a total of 20 factories, which will generate an astonishing 26 trillion data points a year. Assuming 50 bytes at each point, the total amount of data would be 1P, requiring 100 servers. The data isn't just generated in real time, written to storage; Also support fast query, do visual display, help managers to analyze the decision; It can also be used for big data analysis to find deep-seated problems, help enterprises to save energy and reduce emissions, and increase benefits. If a real-time database solution is adopted, the problem can be solved quickly.
Obviously, the real-time database is designed to solve the massive data scenario in the age of 5G and the Internet of Things. However, in the face of massive data scenario, real-time database needs to solve the following problems:
Real-time data writing: How do I support writing high-throughput data points?
Real-time data reading: How to support the grouping and aggregation of hundreds of millions of data in seconds?
Cost sensitive: The problem of cost is brought by mass data storage. How to store these data at a lower cost?
In view of the core pain points of traditional database in the scenario of massive real-time data, such as "high storage cost, high maintenance cost, low write throughput, poor query performance, high data delay", Jixing real-time database effectively solves the above problems through independent technology research and development, and brings more comfortable data use experience for customers:
1. High-speed data writing: support the writing of tens of millions of series data points per second. 2, high throughput data reading: support in the second level of hundreds of millions of data group aggregation operations. 3, high cost performance: with a lower cost to store mass data, low maintenance cost, cost-effective is very obvious in the industry. In addition, Polaris real-time database is also highly matched in the Internet of Things monitoring scenario, can be widely used in the Internet of Things (IoT) equipment monitoring system, enterprise energy management system (EMS), production safety monitoring system, equipment detection system and other scenarios, is the Internet of Things era real-time database choice.
Polaris real-time database, the best choice in the era of Internet of Things
Polaris real-time database is the exclusive research and development of Shenzhen Institute of Digital Research, is a domestic database with fully independent intellectual property rights. The product has a number of real-time data processing patented technology, and through the China Electric Power Research Institute, Guangdong Electric Power Research Institute, China Saibao Laboratory and other authoritative institutions test and verification, excellent performance, leading in China.
The strong performance of Polaris real-time database in the domestic performance is outstanding, by the market hot, has been recognized and trusted by China Southern Power Grid, Three Gorges Power Plant and other top 500 enterprises in the world, the product can be applied to power, petrochemical, transportation, logistics, environmental protection and other more than 10 industries real-time data fusion, storage, analysis and release. If you are interested, please search "Pole Star real-time database", enter the official website for more details, and contact us.
