360 Data View for Government

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Background

Government owned data has been the largest variety of various industries, the largest amount of data. All government departments have a set of data of its own independent systems, and data systems, different types of data are beyond count. Many government agencies, many of these complex data, on the one hand increase the cost of data storage, on the other hand, independent data storage, is greatly affects the efficiency of the cooperation between government departments.

Since 2015, with the rise of big data as a national strategy, the governments at all levels have begun to actively respond to national call to big data technology to improve the government's online platform, improve efficiency, reduce costs, and ultimately benefit the majority of the people.

The city government center, in cooperation with the giant sequoia database, government big data to build a big data sharing platform.

Challenges

Platform using the current architecture and technology is facing many problems:

1) Different data sources and type

The data of the sharing platform is composed of 64 subject tables which are pushed by the subordinate bureaus, this makes the whole system have to set a large number of subject tables but also lower the query efficiency.

The data provided by the Bureau in addition to the structure is not uniform, and the amount of data is relatively large, the number of records is on the billion levels.

2) Unstructured data storage:

Each committee in addition to providing structured data, but also provides unstructured data, such as personal passport, legal certificates and other electronic license. These unstructured data are stored in the same way the various boards are used in the same time, the way of storage management, such as file system storage, database storage, etc.. When these unstructured data is pushed to the shared platform, it is necessary to unify the storage and management, and need to support the application platform for real-time and high concurrent access.

3) Data Sharing Between Platform

In addition to providing efficient query, data analysis and mining are also needed. The traditional data storage architecture, while providing high performance query at the same time, it is difficult to satisfy the demand of data analysis and data mining, and if we build a new storage architecture, it will cause data redundancy, while increasing the cost of inputs.

Advantages brought by SequoiaDB database

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1) Distributed database, massive data access

SequoiaDB supports the way of database service cluster horizontal expansion to improve the performance of database. When you need to store and read the massive data, the performance of the database can be improved by the way of expanding the cluster. Easily achieve dynamic expansion. When a new data node is added to the cluster, it is not necessary to redistribute the data on the existing node.

2) JSON storage and schema-less data structure

SequoiaDB can also support the storage of structured, semi-structured and unstructured data. Data using JSON document model, the data structure can be flexible expansion. Such a storage format, the table of information into a JSON set. In this way, compared with the traditional scheme, the JOIN system is used to improve the random read and write performance.

3) United storage for all systems

At present, more than 1 billion 400 million records in the SequoiaDB cluster, all data will be copied at least 3 copies as a data backup reliability. The system will automatically strip form different replication group on data partitioning to different data nodes, and data access entrance node cluster coordination, according to the data uses the routing access request to the specified data strip, in order to achieve a set of data, a variety of purposes.

4) Fully use of large data analysis framework

Because SequoiaDB can be seamlessly integrated with the Spark/Hadoop cluster, so the sharing platform of data stored in the SequoiaDB, not only can provide real-time online inquiries, can also provide Spark/Hadoop data analysis and mining analysis framework. This can be achieved during the day to run real-time query, batch batch load management mode at night.

Project Result

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To build e-government sharing platform using the giant sequoia database, big data platform of e-government center of the city, has access to more than and 70 units, covering major municipal government departments and 12 districts, the average daily exchange of about 3 million data, collected more than 1 billion 300 million data, paper summarizes the 18 million natural person basic data, 3 million corporate data base the municipal government, the formation of directory information resources sharing, support social security, the flow of personnel management, tax management, small and medium-sized bus control card and other more than and 30 special work, provides the information sharing and business collaboration service for the city's various departments.

Generally speaking, the establishment of government information sharing platform is to promote the application of cross departments information sharing, improve the efficiency of collaboration between departments, improve work efficiency, improve the level of government services.

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SequoiaDB is a financial-level distributed database vendor and is the first Chinese database listed in Gartner’s Magic Quadrant OPDBMS report. SequoiaDB has recently released version 3.0.
SequoiaDB is now penetrating the vertical sector Financial Industry quickly and had more than 50 banking clients and hundreds of enterprise customers in industries including government, telecommunication, Internet and IoT.

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