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Graph database management method

A management method and database technology, applied in inference methods, database indexes, relational databases, etc., can solve problems such as inability to import and integrate multi-graph databases, inability to customize data types, and many restrictions

Pending Publication Date: 2020-08-04
南京安链数据科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most of the existing graph database management can only be added, deleted, modified and checked based on the graph database, and the data type cannot be customized. It can only be created according to the data type in the graph database, which is subject to many restrictions.
The data source import can only be used for text import, and cannot effectively import and integrate data from other data sources into multi-graph databases

Method used

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Embodiment Construction

[0030] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0031] The present invention proposes a graph database management method, which can manage the graph database, from the creation of ontology model, and then complete attribute customization on the graph database basis, multi-graph database management, relational database data import into the graph database, knowledge Query, predictive reasoning, and data products involve the field of big data.

[0032] Such as figure 1 and figure 2 As shown, the graph database management method of the embodiment of the present invention includ...

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Abstract

The invention provides a graph database management method, which comprises the following steps of: newly establishing a knowledge ontology model, adding entity and relationship types into a graph database, then storing structures of the model, the entity and the relationship, and establishing indexes for the structures of the entity and the relationship in ES; after the new model is created, newlyadding entities and relations, storing the entities and relation data in a graph database and a relational database, establishing indexes in ES, starting an import task, importing the data into the graph database through an interface, importing the data mapped by the relations after the entity data is imported, and keeping the data in the graph database; and after the data is stored in the graphdatabase, executing sub-graph display, prediction reasoning and data products. According to the method, data in the relational database can be integrated into the graph database, unified management ofthe multi-graph database is supported, and entity types, relational types, entity data and relational data in the multi-graph database are displayed in a unified mode through knowledge query.

Description

technical field [0001] The invention relates to the technical field of electronic information, in particular to a graph database management method. Background technique [0002] After entering the information age, data has shown explosive growth. The original relational database storage method is a bit difficult to deal with the associated data. As a natural processing relationship, graph database management supports the method of adding, deleting, modifying, and checking (CRUD) to the graph data model. Compared with relational databases and NoSQL storage and processing associated data, graph database management will definitely improve performance. As the data set continues to grow, the performance of relational databases in processing intensive join queries will also deteriorate. Not so with graph databases. Its performance tends to remain constant as the dataset grows larger because the query is only relevant to a portion of the graph. Graph databases are generally us...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06F16/22G06F16/51G06F16/538G06F16/54G06F16/36G06N5/04
CPCG06F16/288G06F16/2228G06F16/51G06F16/538G06F16/54G06F16/367G06N5/04Y02D10/00
Inventor 李林亮彭成铭王娟
Owner 南京安链数据科技有限公司