Relational data management method and apparatus

Abstract

The application discloses a relational data management method, a relational data management device, an electronic device and a storage medium, and belongs to the technical field of data management, wherein the method comprises the following steps: abstracting relational data into a plurality of concept types; establishing an entity attribute table based on each concept type respectively, and storing the entity attribute table into a table database; acquiring an entity relationship between the plurality of concept types and generating a relationship graph; storing the relationship graph into a graph database; and establishing a mapping relationship between the entity attribute table and the relationship graph. The method is to store the entity attributes and the entity relationship contained in the relational data into the table database and the graph database respectively. The decoupling of the entity attributes and the entity relationship in the relational data is realized by establishing the entity attribute table and the relationship graph, the reliability of the relational data management is improved, and the operation resources required by the relational data management are reduced.

Description

Technical Field

[0001] This application belongs to the field of data management technology, specifically relating to a relational data management method, apparatus, electronic device, and storage medium. Background Technology

[0002] Managing relational data typically requires analyzing and storing the attributes and relationships of the data. Traditional relational data management methods usually insert relational information into the corresponding data file pages to achieve relational data management. However, this method suffers from poor database compatibility, increased complexity due to different databases being coupled together, easy accumulation of a large amount of redundant data, and the potential for all data to be lost when some data has problems, resulting in poor reliability. Summary of the Invention

[0003] The purpose of this application is to provide a relational data management method, apparatus, electronic device, and storage medium to solve the problem of poor reliability in existing relational data management.

[0004] According to a first aspect of the embodiments of this application, a relational data management method is provided, the method including:

[0005] Abstract relational data into multiple concept types;

[0006] Entity attribute tables are created for each of the aforementioned concept types, and the entity attribute tables are stored in a table database.

[0007] Obtain the entity relationships between the multiple concept types and generate a relationship graph;

[0008] Store the relationship diagram in a graph database;

[0009] Establish a mapping relationship between the entity attribute table and the relationship graph.

[0010] In some optional embodiments of this application, abstracting relational data into multiple concept types includes:

[0011] Obtain the multiple attribute types contained in the relational data;

[0012] The multiple attribute types are classified and a corresponding concept type is generated for each category.

[0013] In some optional embodiments of this application, establishing an entity attribute table based on each of the concept types includes:

[0014] Generate a table corresponding to the concept type;

[0015] Fill the attribute types sequentially into the header row of the table;

[0016] The entity attribute table is obtained by filling the entity attributes corresponding to the attribute types into the corresponding columns of the table.

[0017] In some optional embodiments of this application, establishing entity attribute tables based on each of the concept types further includes:

[0018] Generate the identifier ID corresponding to the concept type;

[0019] Enter “ID” in the header row of the table;

[0020] Enter the identifier ID into the corresponding column of the table.

[0021] In some optional embodiments of this application, the concept type containing the most attribute types is used as the data type of the relational data;

[0022] Enter the "Data Type" field in the header row of the table;

[0023] Enter the data type into the corresponding column in the table.

[0024] In some optional embodiments of this application, obtaining the entity relationships between the plurality of concept types and generating a relationship graph includes:

[0025] Draw nodes representing each of the stated concept types;

[0026] The relationship diagram is obtained by drawing lines between the nodes to represent the entity relationships.

[0027] In some optional embodiments of this application, the entity attribute table in the table database is converted into tuple data;

[0028] The tuple data is converted into a relational graph and stored in the graph database;

[0029] The tuple data is formed by alternating the concept types and entity relationships.

[0030] In some optional embodiments of this application, the entity relationships in the graph database are clustered, and a table is constructed for each cluster;

[0031] Each tuple data in the graph database is filled into the corresponding table to obtain the entity attribute table, which is then stored in the table database.

[0032] In some optional embodiments of this application, when adding a new entity attribute, a new table record is added to the table database to record the newly added entity attribute;

[0033] When adding a new entity relationship, a connection is added to the graph database to represent the new entity relationship.

[0034] In some optional embodiments of this application, when deleting an entity attribute, the entity attribute is deleted from the table database, and the node and connection corresponding to the entity attribute are deleted from the graph database.

[0035] According to a second aspect of the embodiments of this application, a relational data management device is provided, comprising:

[0036] The abstract module is used to abstract relational data into multiple concept types;

[0037] The entity attribute processing module is used to create entity attribute tables based on each of the concept types and store the entity attribute tables in the table database.

[0038] The acquisition module is used to acquire the entity relationships between the multiple concept types and generate a relationship graph;

[0039] The storage module is used to store the relationship graph into a graph database; the second mapping module is used to establish the mapping relationship between the entity attribute table and the relationship graph.

[0040] According to a third aspect of the embodiments of this application, an electronic device is provided, which may include:

[0041] processor;

[0042] Memory used to store processor-executable instructions;

[0043] The processor is configured to execute instructions to implement the relational data management method as shown in any embodiment of the first aspect.

[0044] According to a fourth aspect of the embodiments of this application, a storage medium is provided, which, when instructions in the storage medium are executed by a processor of an information processing device or a server, enables the information processing device or server to implement the relational data management method as shown in any embodiment of the first aspect.

[0045] The above-mentioned technical solution of this application has the following beneficial technical effects:

[0046] The method described in this application extracts entity attributes and entity relationships from relational data and stores them in a table database and a graph database, respectively. By establishing entity attribute tables and relationship graphs, the entity attributes and entity relationships in relational data are decoupled, improving the reliability of relational data management and reducing the computational resources required for relational data management. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of a relational data management method in an exemplary embodiment of this application;

[0048] Figure 2This is a schematic diagram of the process for establishing an entity attribute table in an exemplary embodiment of this application;

[0049] Figure 3 This is a flowchart illustrating step S105 in an exemplary embodiment of this application;

[0050] Figure 4 This is a schematic diagram illustrating the process of converting a table database to a graph database in an exemplary embodiment of this application;

[0051] Figure 5 This is a schematic diagram of the process of converting a graph database to a table database in an exemplary embodiment of this application;

[0052] Figure 6 This is a flowchart illustrating the process of establishing an entity attribute table in another exemplary embodiment of this application;

[0053] Figure 7 This is a schematic diagram illustrating the process of converting between entity attribute tables and relationship diagrams in an exemplary embodiment of this application;

[0054] Figure 8 This is a flowchart illustrating the process of modifying entity attributes in an exemplary embodiment of this application;

[0055] Figure 9 This is a schematic diagram of the process for modifying entity relationships in an exemplary embodiment of this application;

[0056] Figure 10 This is a schematic diagram of a relational data management device structure according to an exemplary embodiment of this application;

[0057] Figure 11 This is a schematic diagram of the electronic device structure in an exemplary embodiment of this application;

[0058] Figure 12 This is a schematic diagram of the hardware structure of an electronic device in an exemplary embodiment of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of this application. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0060] The accompanying drawings illustrate layer structure diagrams according to embodiments of this application. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0061] Obviously, the described embodiments are only a part of the embodiments of this application, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0062] In the description of this application, it should be noted that the terms "first", "second", and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0063] Furthermore, the technical features involved in the different embodiments of this application described below can be combined with each other as long as they do not conflict with each other.

[0064] The relational data management method, relational data management device, electronic device, and storage medium provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0065] like Figure 1 As shown, in a first aspect of the embodiments of this application, a relational data management method is provided, which may include:

[0066] Step S101: Abstract relational data into multiple concept types;

[0067] Step S102: Create an entity attribute table for each concept type and store the entity attribute table in the table database;

[0068] Step S103: Obtain the entity relationships between multiple concept types and generate a relationship graph;

[0069] Step S104: Store the relationship diagram in the graph database;

[0070] Step S105: Establish the mapping relationship between entity attribute tables and relationship diagrams.

[0071] This embodiment provides a relational data management method that splits the entity attributes and entity relationships contained in relational data and stores them separately in a table database and a graph database, thereby realizing entity modeling of relational data. Relational data can be stored in a relational database. When needed, the corresponding entity attribute table can be queried and maintained based on the mapping relationship between the relational data and the entity attribute table. Similarly, the corresponding relationship graph can be queried and maintained based on the mapping relationship between the relational data and the relationship graph. By establishing entity attribute tables and relationship graphs, the decoupling of entity attributes and entity relationships in relational data is achieved, improving the reliability of relational data management and reducing the computational resources required for relational data management.

[0072] Specifically, step S101 may include: obtaining multiple attribute types contained in the relational data; classifying the multiple attribute types and generating a corresponding concept type for each category. In this embodiment, the multiple attribute types contained in the relational data are sorted out, and similar attribute types are grouped together. In some embodiments, before classifying the multiple attribute types, the multiple attribute types can be filtered to retain numeric and constant attribute types and delete the remaining attribute types. The principle for retaining attribute types is to describe entities as much as possible. Step S102 may include: generating a table corresponding to the concept types; filling the attribute types sequentially into the header row of the table; filling the entity attributes corresponding to the attribute types into the corresponding columns in the table to obtain an entity attribute table.

[0073] In this embodiment, concept types can be entered into the column headers of the table. In some embodiments, the concept type containing the most attribute types is used as the data type of the relational data; the "data type" is entered into the header row of the table; and the data type is entered into the corresponding column in the table. In some embodiments, an identifier ID corresponding to the concept type is generated; the "ID" is entered into the header row of the table; and the identifier ID is entered into the corresponding column in the table. When in use, the entity attribute table can be queried using the unique identifier ID.

[0074] The operation of the example is as follows Figure 2 As shown, data containing attributes such as name and age are abstracted into a "person" type, and data with specific regional attributes are abstracted into a "city" type. The "person" type and the "city" type are conceptual types. In the "person" type, the place of residence refers to the entity of the "city" type. After removing this attribute, the union of the remaining attributes is retained. Li Si has a gender attribute, and the corresponding field should also be created in the table. A "person" attribute table and a "city" attribute table are created to record the mapping relationship between relational data and entity attribute tables.

[0075] This embodiment provides a relational data management method that improves the processing efficiency of relational data by further classifying attribute types to obtain concept types and building tables based on concept types.

[0076] like Figure 3 As shown, specifically, step S105 may include:

[0077] Step S1051: Draw nodes representing each concept type;

[0078] Step S1052: Draw the lines between nodes to represent entity relationships and obtain a relationship diagram.

[0079] This embodiment provides a relational data management method that uses nodes to represent concept types and lines to represent entity relationships. The generated relationship diagram can clearly reflect entity relationships, making it easy to add or delete entity relationships. Independent storage improves the reliability of entity relationship storage.

[0080] like Figure 4 As shown, in some embodiments, it also includes:

[0081] Step S107: Convert the entity attribute table in the table database into tuple data;

[0082] Step S108: Convert the tuple data into a relational graph and store it in the graph database;

[0083] The tuple data is formed by alternating concept types and entity relationships.

[0084] In this embodiment, the tuple data can be triple data, which is formed by sequentially arranging concept type, entity relationship, and concept type.

[0085] like Figure 5 As shown, in some embodiments, it also includes:

[0086] Step S110: Cluster the entity relationships in the graph database and build a table for each cluster;

[0087] Step S111: Fill each tuple data in the graph database into the corresponding table to obtain the entity attribute table and store it in the table database.

[0088] In this embodiment, the tuple data can be triple data, which is formed by sequentially arranging concept type, entity relationship, and concept type.

[0089] Specifically, a triple includes a start relation and an end relation. For example, [concept type_ID1, entity relation, concept type_ID2] represents a relationship between two entities, where the start and end relations are recorded in the form of concept type + table ID. The triple relations are stored in the graph database using the standard graph generation statement SPARQL.

[0090] The operation of the example is as follows Figure 6As shown, Wang Wu's data conforms to the characteristics of a person type and contains the same concept type. A new record is created in the person attribute table, assigned a unique ID, and populated with attribute information. For the 'birthday' in the actual data, a new row title record needs to be created in the person attribute table. The 'residence' attribute matches the existing city type, and the corresponding entity ID 22 is obtained from the city attribute table, thus recording the relation triple [person attribute table_1, residence, city attribute table_22]. The collected triple information is stored in the graph database using the graph database SPARQL statement: 'INSERT DATA{person attribute table_1, residence, city attribute table_22}'.

[0091] In this embodiment, the purpose of converting between graph databases and table databases is to enrich the system's data sources, improve data compatibility, and ensure the system's data portability. Specific implementation methods include:

[0092] Converting a table database to a graph database: Generate triples from each row of the entity attribute table in the table database. The two entity IDs associated with the entity attribute table and the relationship in the entity attribute table form a triple [concept type_ID1, entity relationship, concept type_ID2]. Store the triples in the graph database using SPARQL statements.

[0093] Graph database to table database conversion: Cluster the relationships recorded in the relation graph, build an entity attribute table for each group, and store each triple in the graph database into the row of the corresponding entity attribute table according to the relation name.

[0094] Example operations such as Figure 7 As shown, the transformation between the entity attribute table and the relationship graph is essentially a transformation between row records and triple data. The relationship 'residence' in the entity attribute table is taken as the relationship of the triple, and the two related concept type IDs are taken as two nodes on the graph.

[0095] In some embodiments, when adding an entity attribute, a new row is added to the table database to record the new entity attribute; when adding an entity relationship, a connection is added to the graph database to represent the new entity relationship. When deleting an entity attribute, the entity attribute is deleted from the table database, and the corresponding node and connection are deleted from the graph database. When modifying an entity attribute, the corresponding field in the table database is updated; when modifying an entity relationship, the existing connection in the graph database needs to be deleted, and then a new modified connection needs to be added; when querying an entity attribute or relationship, the corresponding database data can be obtained through mapping.

[0096] Example operation: as shown in the example Figure 8 As shown, to change the age of the character with id=1 to 21, you only need to modify the row record in the entity attribute table; as in the example. Figure 9As shown, to delete the person with id=1 and all its relationships, you only need to delete all edges related to the person 1 node in the relationship graph from the row record in the entity attribute table.

[0097] The relational data management method provided in this embodiment can realize entity modeling of relational data. A graph data structure replaces relational tables, reducing relationship maintenance costs, especially lowering the complexity of relationship maintenance when an entity is deleted. The graph data structure, replacing relational tables, improves query speed and reduces the complexity of multi-table join queries.

[0098] To query relationships by entity attributes, such as finding the residence of student Zhang San's teacher, the SQL syntax in the relationship table is as follows:

[0099] select residence from student table

[0100] LEFT JOIN student-teacher association table ON student table id = association table student id

[0101] left join teacher_table on teacher_table_id = associated_table_teacher_id

[0102] LEFT JOIN teacher-residence-related-table ON teacher-id = related-table teacherid

[0103] left join residence_table on residence_table id = associated_table residence_id

[0104] where student_name = Zhang San;

[0105] In this relational data management method, querying is transformed into three steps (SQL + SPARQL syntax):

[0106] SELECT studentid FROM studenttable WHERE studentname = Zhang San,

[0107] SELECT 'Residence ID' WHERE {'Student ID' < 'Teacher ID' ? ... < 'Residence ID' ? 'Residence ID'}}

[0108] SELECT residence_location FROM residence_location_table WHERE residence_location_id = residence_location_id;

[0109] This query method not only simplifies the syntax and reduces query complexity, but more importantly, users only need to specify what relationship to query, without having to worry about which specific relationship table to query. This advantage is even more obvious when querying complex relationships.

[0110] The separation of entity attributes and entity relationship data reduces the size of the relationship graph, avoids the drawback of large graphs being difficult to split in a distributed environment, and helps to achieve efficient management and maintenance of entity attributes and entity relationships.

[0111] Specifically: When deleting an entity, traditional management methods only use table databases for storage, requiring the deletion of a single row of data corresponding to the entity table, and simultaneously finding and deleting all related table records for that entity. This is very costly when there are many related tables, because users first need to determine which related tables to process; any omissions or errors could have disastrous consequences. However, the relational data management method provided in this embodiment also requires deleting a single row of data corresponding to the entity attribute table, but relationship deletion only requires deleting all relationship connections between the entity through a graph database. The graph database records and maintains the specific relationships involved, greatly reducing manual costs and the probability of errors. For querying complex entity relationships, traditional table database join queries are not only highly complex, but users also need to first understand which related tables are involved, as they only know the relationship to be queried, not the specific associated tables. The relational data management method provided in this embodiment eliminates the concept of relational tables, recording the relationships between entities through a relational graph. This not only achieves data decoupling and enables rapid addition and maintenance of relationships, but also speeds up the querying of complex relationships.

[0112] like Figure 10 As shown, in a second aspect of the embodiments of this application, a relational data management device is provided, comprising:

[0113] Abstract module 11 is used to abstract relational data into multiple concept types;

[0114] The entity attribute processing module 12 is used to create entity attribute tables based on each concept type and store the entity attribute tables in the table database.

[0115] Module 13 is used to obtain entity relationships between multiple concept types and generate a relationship diagram;

[0116] Storage module 14 is used to store the relationship diagram into the graph database; the second mapping module is used to establish the mapping relationship between the entity attribute table and the relationship diagram.

[0117] The relational data management device in this application embodiment can also be a component, integrated circuit, or chip in a terminal. This device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0118] The relational data management device provided in this application embodiment can implement the various processes of the relational data management method provided in any of the above embodiments. To avoid repetition, it will not be described again here.

[0119] Optionally, such as Figure 11 As shown, this application embodiment also provides an electronic device 1100, including a processor 1101, a memory 1102, and a program or instructions stored in the memory 1102 and executable on the processor 1101. When the program or instructions are executed by the processor 1101, they implement the various processes of the above-described relational data management method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0120] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0121] Figure 12 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0122] The electronic device 1200 includes, but is not limited to, components such as: radio frequency unit 1201, network module 1202, audio output unit 1203, input unit 1204, sensor 1205, display unit 1206, user input unit 1207, interface unit 1208, memory 1209, and processor 1210.

[0123] Those skilled in the art will understand that the electronic device 1200 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1210 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 12The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0124] It should be understood that, in this embodiment, the input unit 1204 may include a graphics processing unit (GPU) 12041 and a microphone 12042. The GPU 12041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1206 may include a display panel 12061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 1207 includes a touch panel 12071 and other input devices 12072. The touch panel 12071 is also called a touch screen. The touch panel 12071 may include a touch detection device and a touch controller. Other input devices 12072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here. The memory 1209 can be used to store software programs and various data, including but not limited to applications and operating systems. Processor 1210 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 1210.

[0125] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described relational data management method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0126] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0127] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described relational data management method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0128] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0129] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0130] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0131] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A relational data management method, characterized in that, include: Abstract relational data into multiple concept types; Entity attribute tables are created for each of the aforementioned concept types, and the entity attribute tables are stored in a table database. Obtain the entity relationships between the multiple concept types and generate a relationship graph; Store the relationship diagram in a graph database; Establish a mapping relationship between the entity attribute table and the relationship diagram; Convert the entity attribute table in the table database into tuple data; The tuple data is converted into a relational graph and stored in the graph database, wherein the tuple data is formed by alternating arrangement of the concept types and the entity relations; in, Abstracting relational data into multiple concept types includes: Obtain the multiple attribute types contained in the relational data; The multiple attribute types are classified and a corresponding concept type is generated for each category; Obtaining the entity relationships between the multiple concept types and generating a relationship graph includes: Draw nodes representing each of the stated concept types; The relationship diagram is obtained by drawing lines between the nodes to represent the entity relationships.

2. The relational data management method according to claim 1, characterized in that, Establishing entity attribute tables for each of the aforementioned concept types includes: Generate a table corresponding to the concept type; Fill the attribute types sequentially into the header row of the table; The entity attribute table is obtained by filling the entity attributes corresponding to the attribute types into the corresponding columns of the table.

3. The relational data management method according to claim 2, characterized in that, Establishing entity attribute tables for each of the aforementioned concept types also includes: Generate the identifier ID corresponding to the concept type; Enter "ID" in the header row of the table; Enter the identifier ID into the corresponding column of the table.

4. The relational data management method according to claim 3, characterized in that, Also includes: The concept type containing the most attribute types is taken as the data type of the relational data; Enter the "Data Type" field in the header row of the table; Enter the data type into the corresponding column in the table.

5. The relational data management method according to claim 1, characterized in that, Also includes: Cluster the entity relationships in the graph database and construct a table for each cluster; Each tuple data in the graph database is filled into the corresponding table to obtain the entity attribute table, which is then stored in the table database.

6. The relational data management method according to claim 1, characterized in that, Also includes: When adding a new entity attribute, a new table record is added to the table database to record the newly added entity attribute; When adding a new entity relationship, a connection is added to the graph database to represent the new entity relationship.

7. The relational data management method according to claim 1, characterized in that, Also includes: When deleting an entity attribute, the entity attribute is deleted from the table database, and the corresponding node and connection are deleted from the graph database.

8. A relational data management device, characterized in that, The relational data management device is used to execute the relational data management method as described in any one of claims 1-7, and the relational data management device includes: The abstract module is used to abstract relational data into multiple concept types; The entity attribute processing module is used to create entity attribute tables based on each of the concept types and store the entity attribute tables in the table database. The acquisition module is used to acquire the entity relationships between the multiple concept types and generate a relationship graph; The storage module is used to store the relationship graph into a graph database; the second mapping module is used to establish the mapping relationship between the entity attribute table and the relationship graph.

9. An electronic device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement a relational data management method as described in any one of claims 1-7.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement a relational data management method as described in any one of claims 1-7.

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