Over the recent years, as the information technology in China develops, a varied collection of networks in real life, such as call records, traffic network, power network, social network, financial network, and various interpersonal relationships, are gradually being digitized. These digitized networks are accumulating into big data with graphic architectural features. Effective and in-depth analysis of these data can discover hidden associations and laws, help identify potential problems, optimize network structure, and improve service quality. Applications of these data in the fields like public security and military can directly enhance stability, prevent terrorism, and defend national security. In the financial sector, they can help produce effective anti-money laundering solutions. In the field of social security, they can effectively help find solutions against insurance fraud. And in the field of e-commerce, the data can help form an automatic and effective shopping recommendation system through analyzing the data of the large-scale web structure formed by products and customers. In short, graphic architectural data are extremely valuable in many fields.
In 2015, the US Department of Defense included a computational model study of human behavior based on social networks into one of the six major subversive basic research areas in the future.
Facing the need for real-time query processing of hyper large-scale graphic architectural data, the relational database management systems that have been dominant for decades are now challenged directly. In order to analyze the associations between multiple intervals, the response time of the relational database is often measured in hours or days; and as the intervals of the relationship increase, the response time grows geometrically. This renders the relational database utterly inapplicable.
The global NoSQL market keeps growing at a compound annual growth rate of 30% from 2015 to 2020 and is expected to reach USD 4 billion.
We hosted a workshop on the subject of efficient processing of hyper large-scale graphic architectural data. In the workshop we met representatives from sci-tech enterprises like the 28th Research Institute of China Electronics Technology Group Corporation, Dameng Database Company, Sichuan Jiuzhou Company and Objectivity, and potential users in such fields as military, public security, telecommunications, transportation and energy, as well as investment institutions such as CECEP Technology Investment Co., Ltd. In the workshop, representatives from potential users and system integration companies expressed their desire to use graphic architectural data processing technology to explore potential information value based on their application of big data in their respective fields,
However, there are currently no mature products on the Chinese market due to the high technical difficulty in the processing of such data. As a result, the needs of more and more in-depth applications have yet to be met.
Implementation Solutions
The solutions include introducing the world's top super large-scale graphic architectural data processing technology; combining with relevant channels, technology, capital and other resources; setting up entities in Qingdao Oceantec Valley to drive the rapid development of China's graphic architectural data processing technology and applications.
After extensive investigation, QDII chose to work with Objectivity to quickly crack the market through introduction, optimization and localization, and become bigger and stronger in the field of efficient processing of super large-scale graphic architectural data. Objectivity is a global leader in large-scale graphic architectural data processing. Over the past three decades, it has been dedicated to technical research and product development in this field. The core product ThingSpan is an enterprise-class product featuring high concurrency, high scalability, high efficiency and flexible deployment. The processing efficiency is 2 orders of magnitude higher than the efficiency of traditional relational databases. Objectivity’s customers are scattered in the US government, military and telecommunications, finance, manufacturing, Internet, medical and health industries, including many Fortune 500 companies, which ensures favorable application effect of its technologies and considerable economic benefits.
QDII integrates quality resources at home and abroad, and builds entities to create a new stronghold for super large-scale graphic architectural data processing technology. Specifically, a joint venture consisting of Objectivity, system integrators with channel resources, and investors (QDII’s industrial fund and other investment institutions) is to be founded.
The parties will invest in different ways within a certain period of time (2 to 3 years), and get the corresponding equity ratio in the joint venture in return.
Objectivity: Packaging system software license and corresponding services;
System integrator: Market channel and capacity of system integration (and relevant qualifications);
Investor: In cash.
System Tests
To ensure the cutting-edge advantage of Objectivity, we have conducted independent and comprehensive tests after coordinating with Dameng Database and Objectivity respectively. The tests were performed for the same test scenario in a similar hardware environment.
The tests, based on the use cases in actual production, utilize the analog data which has the same scale (tens of billions of data records) as the production environment, and is generated after the sensitive information is eliminated. The tested cases include the loading of massive data and the query of the multi-interval relationship. The tests were performed in a parallel computing environment composed of multiple servers in the LAN. The test results indicate that:
The Objectivity system can efficiently process queries for any degrees (5°, 6°, or more) interval associations of massive data sets. Regardless of how the interval increases, the response time is in the second order (mostly less than 1 minute). While the current relational database-based production system can only handle queries within a 3° interval, queries for associations above 3° interval often take several days of processing time.
Objectivity's object-oriented query language DO can express arbitrarily complex web structure logic. For example, starting from one point, look for the associated nodes at intervals of 1°, 2°, or even more according to the given conditions; and given two points, find all paths according to the given conditions. This is far beyond the expressive power of SQL.
Objectivity is also more efficient in loading mass data into the databank than the currently available production systems.
Conclusions
The global application market for super large-scale graphic architectural data processing technology is growing at a rate of over 30%. And this is also evidenced by the need of this technology in the sensitive fields such as public security, national security, and national defense, as well as civilian fields like health, insurance, finance, electricity and traffic. The core technology of Objectivity was originally an object-oriented database management system that has been refined for nearly three decades. Its internal technological mechanism is in complete agreement with the technical requirements for dealing with super large-scale complex graphic architectural data in recent years, so it can benefit from years of technology accumulation and gain the first-mover advantage in the emerging markets.
QDII is now looking for system integrators and investors with channel resources, with the intention of working with the parties to introduce Objectivity technology and meet the urgent needs of customers in relevant industries as quickly as possible.