Highly intelligent multi-environment data synchronization system and implementation method thereof

Abstract

The invention discloses a highly-intelligent multi-environment data synchronization system and an implementation method thereof, belongs to the technical field of data synchronization, and remarkably improves the data synchronization efficiency and reliability through the highly-intelligent multi-environment data synchronization system. Through an intelligent structural difference detection technology, the system can recognize and adapt to changes of objects such as database table structures, views and indexes in real time, DDL statements conforming to target environment specifications are automatically generated, and the tedious process that a traditional tool depends on manual adjustment is avoided. Through combination of multi-thread concurrent processing and an incremental synchronization strategy, a time window of large-scale data synchronization is greatly shortened, and service continuity is ensured not to be affected. Meanwhile, a conflict resolution mechanism and a data verification function are built in the system, so that the integrity and consistency of the data in the transmission process are effectively guaranteed, and the business risk caused by data dislocation or loss is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of data synchronization, and specifically relates to a highly intelligent multi-environment data synchronization system and an implementation method thereof. Background Art

[0002] In software development and maintenance, ensuring consistency of software functionality across different environments (such as development, testing, and production) is crucial. Data synchronization, a key component of this process, directly impacts software stability and reliability. Data synchronization involves automatically replicating and updating data between different devices, systems, or databases using specific technologies and protocols to ensure data consistency and real-time performance. Data synchronization is widely used in various scenarios, such as between mobile devices and servers, between distributed databases, and between cloud services and local storage. Data synchronization can be implemented in a variety of ways, including real-time, scheduled, and manual. Real-time synchronization replicates changes to the target location immediately upon data change, ensuring real-time performance. Scheduled synchronization replicates data at preset intervals and is suitable for scenarios where real-time performance is less critical. Manual synchronization requires users to manually trigger the data replication operation. Data synchronization processes must consider factors such as conflict resolution, data security and integrity, network bandwidth, and latency. Common data synchronization technologies include log-based replication, timestamp-based synchronization, and trigger-based synchronization. Through data synchronization, data sharing and collaboration can be achieved, work efficiency can be improved, and data reliability and availability can be ensured.

[0003] However, existing data synchronization tools have the following shortcomings when handling multi-environment data synchronization:

[0004] 1. Poor adaptability to table structure changes: Existing tools typically rely on static field mapping configurations and are unable to dynamically detect and adapt to changes in table structures between the source and target databases.

[0005] 2. Existing synchronization tools often only focus on synchronizing table structures and ignore the synchronization requirements for non-table objects, resulting in inconsistencies in the database environment and affecting the normal operation of software functions.

[0006] 3. When faced with large-scale data sets, existing synchronization tools often use a single-threaded synchronization approach, resulting in long synchronization cycles and a significant impact on business operations. Furthermore, the lack of efficient synchronization algorithms and optimization methods makes it difficult to improve synchronization efficiency.

[0007] 4. Inadequate error handling and recovery capabilities: When errors occur during synchronization, existing tools often only provide simple error prompts and lack automated error analysis and recovery mechanisms. This results in operations and maintenance personnel spending a significant amount of time troubleshooting and manually recovering, increasing both the difficulty and cost of operations and maintenance.

[0008] 5. Lack of data rollback methods: If synchronization fails or data inconsistencies occur, existing tools often fail to provide effective data rollback methods. This can lead to data loss or corruption, severely impacting business operations. Summary of the Invention

[0009] The purpose of the present invention is to provide a highly intelligent multi-environment data synchronization system and its implementation method in order to solve the above-mentioned problems.

[0010] The technical solution adopted by the present invention is as follows: a highly intelligent multi-environment data synchronization system, comprising: an intelligent structure difference detection and DDL generation module, a data synchronization engine module, an error handling and recovery module, a snapshot management and rollback module, a user interface and API module, a security and permission management module, and an extension and integration module;

[0011] The intelligent structure difference detection and DDL generation module is internally provided with a metadata scanning module, a difference comparison module and a DDL statement automatic generation module;

[0012] The DDL execution interface of the intelligent structure difference detection and DDL generation module is connected to the structure synchronization interface of the data synchronization engine module;

[0013] The task status output terminal of the data synchronization engine module is directly connected to the error monitoring input terminal of the error processing and recovery module;

[0014] The recovery strategy execution end of the error handling and recovery module is reversely connected to the task retry interface of the data synchronization engine module; the rollback operation interface of the snapshot management and rollback module receives user-triggered rollback requests through the user interface and the control instruction input end of the API module, and its snapshot metadata end is connected to the audit log interface of the security and rights management module;

[0015] The task configuration output end of the user interface and API module is directly connected to the policy loading interface of the data synchronization engine module, and its API communication end is bound to the identity authentication interface of the security and rights management module;

[0016] The database driver adapter of the extension and integration module is embedded in the data connection pool of the data synchronization engine module;

[0017] The security and rights management module covers the external communication interface of the user interface, API and data synchronization engine through the encrypted channel end.

[0018] In a preferred embodiment, the metadata scanning module includes a real-time metadata scanning engine and metadata storage structure. The scanning engine parses the definitions of objects such as tables, views, and indexes. The storage structure uses a hash table or tree structure for fast data access, supporting cross-database version and type adaptation.

[0019] In a preferred embodiment, the difference comparison module incorporates a fast hashing algorithm and a deep difference analyzer. The hashing algorithm generates unique object identifiers and provides a preliminary assessment of differences, while the deep analyzer analyzes details such as field additions and deletions, and constraint changes layer by layer, generating a report containing the difference types and impacts.

[0020] In a preferred embodiment, the DDL statement automatic generation module is internally equipped with a syntax-compatible generator and a custom template engine. The generator outputs DDL statements that conform to the target database specification based on the difference report, and the syntax is checked to ensure feasibility. The custom template engine supports user-defined specific rules and logical extensions.

[0021] In a preferred embodiment, the data synchronization engine module internally houses a multi-threaded task scheduler, incremental synchronization components, full synchronization components, and a data validation and conflict resolver. The task scheduler dynamically allocates thread resources based on a priority queue. The incremental synchronization component tracks changes through change data capture or synchronization logs, and the full synchronization component is responsible for completely replicating the source database content. The data validation and conflict resolver incorporates a built-in hash validation mechanism and policy library, supporting various conflict handling rules such as overwrite, retention, and merging.

[0022] In a preferred embodiment, the error handling and recovery module is internally equipped with an intelligent error recognition engine, an automatic recovery executor, and an error log management system. The intelligent error recognition engine categorizes error types such as database connection failures and permission exceptions and generates detailed reports. The automatic recovery executor has a built-in strategy library for reconnection and format conversion. The error log management system stores logs in a distributed database and supports multi-dimensional querying.

[0023] In a preferred embodiment, the snapshot management and rollback module includes a snapshot generator, a snapshot metadata manager, and a one-click rollback engine. The snapshot generator automatically creates a complete copy of the database before synchronization and stores it in cloud storage or a distributed file system. The snapshot metadata manager records the version, timestamp, and storage path. The one-click rollback engine supports rapid data recovery and generates verification reports.

[0024] In a preferred embodiment, the user interface and API module are internally configured with a visual web console and a standardized RESTful API interface. The web console provides task configuration, progress monitoring, and log query functions, while the RESTful API interface provides capabilities such as task management and snapshot operations. All requests are subject to security verification and encrypted transmission.

[0025] In a preferred embodiment, the security and rights management module incorporates an authentication and authorization mechanism, a data transmission encryption layer, and an audit log system. Authentication supports the OAuth 2.0 protocol and role-based permissions, while data transmission encryption utilizes TLS 1.3 and the AES-256 algorithm. The audit log system records user actions and supports behavior tracing.

[0026] The expansion and integration module is internally equipped with multiple database adapters and a plug-in extension framework. The multiple database adapters are compatible with mainstream database types such as MySQL and Oracle. The plug-in extension framework allows for custom synchronization strategies and data conversion rules and interconnection with the intelligent structure detection module.

[0027] In a preferred embodiment, a method for implementing a highly intelligent multi-environment data synchronization system includes the following steps:

[0028] S1: Deploy the metadata scanning engine of the intelligent structure difference detection module, configure real-time or scheduled scanning of tables, views, indexes and other objects in the source and target databases, extract fields and constraint definitions and store them as hash structures;

[0029] S2: Enable the hash and deep analysis algorithms of the difference comparison module to identify library structure differences and generate a detailed report. Link the DDL statement automatic generation module to output syntax statements compatible with the target environment.

[0030] S3: Configure a multi-threaded task scheduler in the data synchronization engine module, set the change capture mechanism for incremental synchronization and the complete replication strategy for full synchronization, and load the conflict resolution rule library;

[0031] S4: An intelligent recognition engine that integrates error handling and recovery modules deploys automatic reconnection and format conversion strategies, and binds to the snapshot management module to implement automatic snapshot creation and rollback triggering conditions before synchronization;

[0032] S5: Deploy a visual console through the user interface and API module, open task configuration and progress tracking functions, and enable the RESTful API interface for encrypted calls from external systems;

[0033] S6: Activate the OAuth2 authentication and TLS encryption channel of the security and permission management module, and configure the multi-database driver adapter and plug-in extension framework of the extension module.

[0034] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0035] 1. In the present invention, the efficiency and reliability of data synchronization are significantly improved through a highly intelligent multi-environment data synchronization system. Through intelligent structural difference detection technology, the system can identify and adapt to changes in database table structures, views, indexes and other objects in real time, and automatically generate DDL statements that meet the specifications of the target environment, avoiding the cumbersome process of traditional tools relying on manual adjustments. The combination of multi-threaded concurrent processing and incremental synchronization strategy greatly shortens the time window for large-scale data synchronization, ensuring that business continuity is not affected. At the same time, the system's built-in conflict resolution mechanism and data verification function effectively ensure the integrity and consistency of data during transmission, reducing business risks caused by data dislocation or loss. This highly automated design significantly reduces the manual operation requirements of operation and maintenance personnel and improves the intelligence level of the overall synchronization process.

[0036] 2. In the present invention, the reliability of data protection is further enhanced through multiple security mechanisms and fault-tolerant designs. The snapshot management function automatically generates a data backup before each synchronization and supports one-click rollback to the historical state, providing a bottom-line guarantee for data security. Intelligent error identification and recovery strategies can quickly respond to abnormal situations during the synchronization process, such as automatically reconnecting to the database or converting the data format, minimizing the delay of manual intervention. The security module ensures the security of data in the entire link of transmission, storage and recovery through end-to-end encryption, fine-grained permission control and operation audit logs. These features not only enhance the system's risk resistance, but also enable it to adapt to the stringent requirements of highly sensitive scenarios such as finance and government affairs, building an efficient and reliable multi-environment data synchronization solution for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a block diagram of the overall system of the present invention;

[0038] Figure 2 This is a system block diagram of the intelligent structure difference detection and DDL generation module in the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0040] Example:

[0041] Reference Figure 1-2, a highly intelligent multi-environment data synchronization system, including: intelligent structure difference detection and DDL generation module, data synchronization engine module, error handling and recovery module, snapshot management and rollback module, user interface and API module, security and permission management module and extension and integration module;

[0042] The intelligent structure difference detection and DDL generation module is internally configured with a metadata scanning module, a difference comparison module, and a DDL statement automatic generation module;

[0043] The DDL execution interface of the intelligent structure difference detection and DDL generation module is connected to the structure synchronization interface of the data synchronization engine module;

[0044] The task status output terminal of the data synchronization engine module is directly connected to the error monitoring input terminal of the error processing and recovery module;

[0045] The recovery strategy execution end of the error handling and recovery module is reversely connected to the task retry interface of the data synchronization engine module; the rollback operation interface of the snapshot management and rollback module receives user-triggered rollback requests through the user interface and the control instruction input end of the API module. At the same time, its snapshot metadata end is connected to the audit log interface of the security and permission management module.

[0046] The task configuration output of the user interface and API module is directly connected to the policy loading interface of the data synchronization engine module, and its API communication end is bound to the identity authentication interface of the security and rights management module;

[0047] The database driver adapter of the extension and integration module is embedded in the data connection pool of the data synchronization engine module;

[0048] The security and permission management module covers the external communication interfaces of the user interface, API and data synchronization engine through encrypted channels.

[0049] The metadata scanning module uses a built-in efficient scanning engine to perform in-depth analysis of the source and target databases in real time or on a scheduled basis, comprehensively collecting all types of database object information, including table structure, view definition, index structure, stored procedure code, trigger logic, and function definition. During the scanning process, the module uses an optimized metadata extraction algorithm to accurately capture key definition details such as field names, data types, primary keys and foreign key constraints, and stores the parsed metadata in memory in a hash table or tree structure to ensure fast access and efficient management. The module supports multiple database types and versions, and can dynamically adapt to the differences in metadata formats of different databases, providing standardized and structured metadata input for subsequent difference comparisons. The scanning results are updated in real time to ensure that the system always performs synchronization operations based on the latest database status, reducing the risk of synchronization failures due to metadata lags.

[0050] The difference comparison module uses a dual algorithm based on hash values ​​and deep comparison to achieve efficient difference detection. The module first generates a unique hash value for each database object. The hash value is calculated based on the definition information of the object. By quickly comparing the hash values ​​of the corresponding objects in the source database and the target database, it preliminarily determines whether there are structural differences. If the hash values ​​are inconsistent, the module further performs in-depth analysis, parsing complex differences such as field additions and deletions, data type changes, primary key and foreign key adjustments in the table structure layer by layer, and accurately identifies definition differences in non-table objects such as views, indexes, and stored procedures. The difference report lists in detail the type, difference content, and impact scope of all inconsistent objects, such as missing fields, constraint conflicts, or code logic changes, providing an accurate basis for DDL generation. The module's intelligent algorithm can distinguish between necessary and unnecessary differences, avoid misjudgments due to differences in database versions or configurations, and improve the accuracy and practicality of the comparison results.

[0051] The automatic DDL statement generation module intelligently generates DDL statements that comply with the target database's syntax specifications based on difference reports. These statements cover operations such as table structure modifications, view reconstruction, index adjustments, and stored procedure updates. The module includes built-in syntax and semantic checking mechanisms to ensure that the generated statements can be correctly executed in the target database, for example, avoiding duplicate field additions, illegal data type conversions, or constraint violations. The module also supports user-defined DDL templates, allowing you to define specific syntax rules or expand synchronization logic based on business needs, such as adding comments, adjusting field order, or integrating custom validation logic. During the generation process, the module dynamically adapts to the target database's version characteristics and configuration parameters to ensure cross-platform compatibility. Generated DDL statements are optimized and arranged in execution order, prioritizing objects with lower dependencies to avoid synchronization interruptions caused by incorrect execution order. The module also provides a pre-execution simulation function, allowing users to verify the integrity and security of DDL logic before formal execution, further reducing synchronization risks.

[0052] The data synchronization engine module adopts a multi-threaded concurrent processing mechanism, dynamically allocates thread resources based on the task queue to maximize synchronization efficiency, and supports flexible adjustment of thread allocation according to task priority and data volume. The module provides two strategies: incremental synchronization and full synchronization. Incremental synchronization only synchronizes data that has changed since the last synchronization by recording synchronization logs or using the database's change data capture function, while full synchronization copies all data from the source database to the target environment. During the synchronization process, the module has a built-in hash-based data verification mechanism to ensure data integrity and consistency, and is equipped with a conflict resolution strategy library that supports preset strategies such as overwriting, retention, and merging, or user-defined rules to handle primary key conflicts, format mismatches, and other issues. The status of all synchronization tasks is pushed to the error handling module in real time, and snapshot generation is triggered before startup to ensure that the task is traceable and recoverable.

[0053] The error handling and recovery module automatically classifies the types of errors during the synchronization process through an intelligent error recognition engine, including database connection failure, data format abnormalities, insufficient permissions, etc., and generates a detailed error report containing the time, type, cause, and scope of impact. The module has a built-in recovery strategy library that automatically performs operations such as reconnecting to the database, format conversion, and permission application for different errors. If automatic recovery fails, the error information is recorded and an alarm is pushed to the user interface. All error logs are stored in a distributed database or log file system, and support multi-dimensional query and export by time range, error type, etc. through the user interface, making it easier for operation and maintenance personnel to analyze the root cause and optimize the synchronization process. The module is bidirectionally connected to the data synchronization engine, receives task exception signals in real time, and reschedules tasks after recovery.

[0054] The snapshot management and rollback module automatically creates a snapshot of the source database before each synchronization operation, completely preserving the table structure and data status. The snapshot is stored in cloud storage or distributed file systems and records metadata such as versions and timestamps to support version traceability. When synchronization fails or data is inconsistent, users can trigger a one-click rollback through the interface or API. The system automatically verifies the target environment status and restores the data based on the snapshot. The rollback process generates a detailed report listing the recovery results and potential problem suggestions. All rollback operations are recorded as audit logs by the security module, and the snapshot metadata and storage path are encrypted and protected to ensure data security and operational compliance. This module works in conjunction with the data synchronization engine to ensure that data can be rolled back before the task is started, and quickly responds to recovery needs when the user intervenes.

[0055] The user interface and API module provide a visual web console and a standardized RESTful API interface. The web interface supports configuring synchronization task parameters, selecting incremental or full mode, defining conflict resolution rules and customizing DDL templates. The real-time monitoring dashboard displays task progress, resource utilization, and error alarm information. The log query function supports filtering records by time and error type. The API interface opens up functions such as task management, snapshot operations, and log retrieval to facilitate integration with external systems. All API requests must pass the identity authentication and transmission encryption of the security module. User operation instructions are passed to the data synchronization engine loading strategy through the interface or API. At the same time, the rollback request is directly connected to the snapshot module to trigger the recovery process, forming a closed-loop control.

[0056] The security and permission management module implements a multi-level protection mechanism. Identity authentication supports the OAuth 2.0 protocol and JWT token verification. Role permissions are subdivided into administrators, operators, and read-only users to control the scope of functional access. Data transmission uses TLS1.3 encryption, and snapshot storage and error logs are encrypted using the AES-256 algorithm to ensure static data security. The audit log module records all user operations, including task configuration, rollback execution, and permission changes, and supports tracing behavior tracks by operation type and timestamp. This module covers the user interface, API, and external communication interfaces of the data synchronization engine, while implementing encryption control on snapshot storage and log storage to form an end-to-end security protection system.

[0057] The Extension and Integration module provides multiple database adapters and a plug-in extension framework for mainstream databases such as MySQL, PostgreSQL, and Oracle, ensuring cross-platform data synchronization through driver compatibility. The plug-in framework allows users to develop custom plug-ins, such as adding new synchronization strategies, data conversion rules, or extending DDL generation templates. Plugins connect to the intelligent structure difference detection module via standardized interfaces, dynamically enhancing system functionality. The module's data connection pool is embedded in the data synchronization engine, supporting high-concurrency access to different database types. It also exposes extensibility through an API, reducing system coupling and improving business adaptability.

[0058] A highly intelligent multi-environment data synchronization system implementation method includes the following steps:

[0059] S1: Deploy the metadata scanning engine of the intelligent structure difference detection module, configure real-time or scheduled scanning of tables, views, indexes and other objects in the source and target databases, extract fields and constraint definitions and store them as hash structures;

[0060] S2: Enable the hash and deep analysis algorithms of the difference comparison module to identify library structure differences and generate a detailed report. Link the DDL statement automatic generation module to output syntax statements compatible with the target environment.

[0061] S3: Configure a multi-threaded task scheduler in the data synchronization engine module, set the change capture mechanism for incremental synchronization and the complete replication strategy for full synchronization, and load the conflict resolution rule library;

[0062] S4: An intelligent recognition engine that integrates error handling and recovery modules deploys automatic reconnection and format conversion strategies, and binds to the snapshot management module to implement automatic snapshot creation and rollback triggering conditions before synchronization;

[0063] S5: Deploy a visual console through the user interface and API module, open task configuration and progress tracking functions, and enable the RESTful API interface for encrypted calls from external systems;

[0064] S6: Activate the OAuth2 authentication and TLS encryption channel of the security and permission management module, and configure the multi-database driver adapter and plug-in extension framework of the extension module.

[0065] From the above we can know:

[0066] In this invention, the data synchronization efficiency is significantly improved:

[0067] Multi-threaded concurrent processing: By using multi-threaded concurrent technology, the system can handle multiple data synchronization tasks simultaneously, significantly improving synchronization efficiency. This concurrent processing method enables the system to complete large amounts of data synchronization in a short period of time, reducing the time and resource costs required for synchronization.

[0068] Incremental / Full Synchronization Strategy: The system supports both incremental and full synchronization modes. Users can choose the appropriate synchronization mode based on their needs. Incremental synchronization mode only synchronizes data that has changed since the last synchronization, significantly reducing the amount of data synchronized and further improving synchronization efficiency.

[0069] In the present invention, the intelligence and automation level of data synchronization are enhanced:

[0070] Intelligent Structural Difference Detection and DDL Generation: The system automatically detects structural differences between the source and target databases and generates DDL statements that conform to the target database specifications. This feature not only reduces manual operations but also improves synchronization accuracy and reliability.

[0071] Intelligent recovery strategy: The system has a built-in intelligent error recognition engine and recovery strategy that automatically identifies the type and cause of errors during synchronization and attempts to recover automatically. This reduces the risk of synchronization failure and improves system stability and availability.

[0072] In the present invention, the reliability and security of data synchronization are improved:

[0073] Data Verification and Conflict Resolution: During synchronization, the system uses a hash-based data verification mechanism to ensure data integrity and consistency. The system also provides a variety of conflict resolution strategies, such as overwrite, retain, and merge, to address potential data conflicts.

[0074] Snapshot Management and Data Rollback: The system supports snapshot creation and storage, enabling rapid recovery of database status in the event of synchronization failures or data inconsistencies. This feature provides additional security for data synchronization and reduces the risk of data loss or corruption.

[0075] In the present invention, the operation and maintenance costs and difficulty are reduced:

[0076] Intuitive and easy-to-use user interface: The system provides an intuitive and easy-to-use web user interface, through which users can easily configure synchronization tasks, view synchronization progress, query error logs, and perform other operations. This reduces the learning cost for operation and maintenance personnel and improves the ease of use of the system.

[0077] Flexible Scalability: The system utilizes a microservices architecture, with modules communicating and collaborating via RESTful APIs. This architecture allows for flexible resource adjustments based on business needs, supporting both horizontal and vertical scalability. Furthermore, the system supports API calls, facilitating integration and collaboration with other systems, reducing maintenance complexity and costs.

[0078] In this invention, business continuity and data consistency are improved:

[0079] Real-time data synchronization: The system supports real-time data synchronization, ensuring data consistency between the source and target databases. This helps improve business continuity and reliability, avoiding business interruptions or errors caused by inconsistent data.

[0080] Cross-platform support: The system supports a variety of database types and operating system platforms, making it easy to synchronize data across platforms. This provides users with more choices and flexibility, helping to improve the system's compatibility and adaptability.

[0081] In summary, the technical solution proposed in this invention offers significant advantages and benefits in the field of multi-environment data synchronization. By improving synchronization efficiency, enhancing intelligence and automation, improving reliability and security, reducing operational costs and maintenance difficulties, and improving business continuity and data consistency, this invention brings new breakthroughs and progress to the field of data synchronization.

[0082] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements that are inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0083] The above description is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A highly intelligent multi-environment data synchronization system, characterized by: Said include: Intelligent structure difference detection and DDL generation module, data synchronization engine module, error handling and recovery module, snapshot management and rollback module, user interface and API module, security and permission management module, and extension and integration module; The intelligent structure difference detection and DDL generation module is internally provided with a metadata scanning module, a difference comparison module and a DDL statement automatic generation module; The DDL execution interface of the intelligent structure difference detection and DDL generation module is connected to the structure synchronization interface of the data synchronization engine module; The task status output terminal of the data synchronization engine module is directly connected to the error monitoring input terminal of the error processing and recovery module; The recovery strategy execution end of the error handling and recovery module is reversely connected to the task retry interface of the data synchronization engine module; the rollback operation interface of the snapshot management and rollback module receives user-triggered rollback requests through the user interface and the control instruction input end of the API module, and its snapshot metadata end is connected to the audit log interface of the security and rights management module; The task configuration output end of the user interface and API module is directly connected to the policy loading interface of the data synchronization engine module, and its API communication end is bound to the identity authentication interface of the security and rights management module; The database driver adapter of the extension and integration module is embedded in the data connection pool of the data synchronization engine module; The security and rights management module covers the external communication interface of the user interface, API and data synchronization engine through the encrypted channel end.

2. A highly intelligent multi-environment data synchronization system as claimed in claim 1, characterized in that: The metadata scanning module is internally provided with a real-time metadata scanning engine and a metadata storage structure; the scanning engine parses the definition information of tables, views, and index objects, and the storage structure uses a hash table or tree form to quickly access data and supports cross-database version and type adaptation.

3. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The difference comparison module is internally provided with a hash fast comparison algorithm and a deep difference analyzer; The hash algorithm generates a unique identifier for the object and preliminarily determines the differences. The deep analyzer analyzes the details of field additions and deletions and constraint changes layer by layer, and generates a report that includes the difference type and impact.

4. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The DDL statement automatic generation module is internally provided with a syntax-compatible generator and a custom template engine; the generator outputs DDL statements of the target database specification based on the difference report, and the syntax check ensures the feasibility of execution. The custom template engine supports user-defined specific rules and logical extensions.

5. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The data synchronization engine module is internally equipped with a multi-threaded task scheduler, an incremental synchronization component, a full synchronization component, and a data checker and conflict resolver; the task scheduler dynamically allocates thread resources based on a priority queue, the incremental synchronization component tracks changed data through change data capture or synchronization logs, and the full synchronization component is responsible for completely replicating the source database content; The data validation and conflict resolver has a built-in hash validation mechanism and policy library, which supports overwriting, retaining, and merging of multiple conflict handling rules.

6. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The error handling and recovery module is internally provided with an intelligent error recognition engine, an automatic recovery executor and an error log management system; The intelligent error recognition engine classifies database connection failures and permission exception error types and generates detailed reports. The automatic recovery executor has a built-in reconnection and format conversion strategy library. The error log management system stores logs in a distributed database and supports multi-dimensional queries.

7. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The snapshot management and rollback module is internally equipped with a snapshot generator, a snapshot metadata manager and a one-key rollback engine; the snapshot generator automatically creates a complete copy of the database before synchronization and stores it in cloud storage or a distributed file system, the snapshot metadata manager records the version, timestamp and storage path, and the one-key rollback engine supports rapid data recovery and generates verification reports.

8. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The user interface and API module are internally provided with a visual web console and a standardized RESTful API interface; the web console provides task configuration, progress monitoring and log query functions, and the RESTful API interface opens up task management and snapshot operation capabilities. All requests must pass security verification and encrypted transmission.

9. The highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The security and rights management module is internally equipped with an identity authentication and authorization mechanism, a data transmission encryption layer, and an audit log system; identity authentication supports the OAuth 2.0 protocol and role-based hierarchical permissions, data transmission encryption uses TLS1.3 and AES-256 algorithms, and the audit log system records user operations and supports behavior tracing; The expansion and integration module is internally provided with multiple database adapters and a plug-in expansion framework; The multi-database adapter is compatible with mainstream database types such as MySQL and Oracle, and the plug-in extension framework allows customization of synchronization strategies, data conversion rules, and interconnection with the intelligent structure detection module.

10. The method for implementing a highly intelligent multi-environment data synchronization system according to claim 1, characterized in that: The method comprises the following steps: S1: Deploy the metadata scanning engine of the intelligent structure difference detection module, configure real-time or scheduled scanning of the tables, views, and index objects of the source and target databases, extract the fields and constraint definitions, and store them as hash structures; S2: Enable the hash and deep analysis algorithms of the difference comparison module to identify library structure differences and generate a detailed report. Link the DDL statement automatic generation module to output syntax statements compatible with the target environment. S3: Configure a multi-threaded task scheduler in the data synchronization engine module, set the change capture mechanism for incremental synchronization and the complete replication strategy for full synchronization, and load the conflict resolution rule library; S4: An intelligent recognition engine that integrates error handling and recovery modules deploys automatic reconnection and format conversion strategies, and binds to the snapshot management module to implement automatic snapshot creation and rollback triggering conditions before synchronization; S5: Deploy a visual console through the user interface and API module, open task configuration and progress tracking functions, and enable the RESTful API interface for encrypted calls from external systems; S6: Activate the OAuth2 authentication and TLS encryption channel of the security and permission management module, and configure the multi-database driver adapter and plug-in extension framework of the extension module.

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