Evaluation method and system of domestic database migration evaluation tool

Abstract

The invention relates to the technical field of database migration, in particular to an evaluation method and system for a domestic database migration evaluation tool, and the method comprises the following steps: data collection, source library analysis, target library recommendation and report generation. The method has the beneficial effects that the automation degree is high, manual intervention is reduced, and the complexity and error rate of evaluation are reduced; the evaluation result has multiple dimensions and covers multiple aspects of compatibility, migration workload and the like; the application range is wide, and the method can be applied to migration evaluation of various domestic databases; and the technical threshold of database migration evaluation is reduced, so that non-professional technicians can also carry out preliminary evaluation work.

Description

Technical Field

[0001] The present invention relates to the technical field of database migration, and specifically to an evaluation method and system for a domestic database migration evaluation tool. Background Art

[0002] According to the requirements of domestic substitution, with the development of domestic database technology, more and more business systems are starting to migrate their existing databases to domestic databases to improve data security and the ability of self-control.

[0003] However, due to the differences between different database systems, direct migration often faces many challenges, including data type mismatches, SQL syntax differences, performance bottlenecks, etc. Most traditional evaluation methods rely on manual analysis. For example, calculating the workload according to function points lacks a scientific basis and has a large error in evaluating the real workload. Therefore, an effective evaluation tool is crucial for predicting the feasibility and workload of domestic database migration. Summary of the Invention

[0004] The purpose of the present invention is to provide an evaluation method and system for a domestic database migration evaluation tool, which evaluates the feasibility, workload, and potential risks of migration by automatically analyzing the differences between the source database and the target domestic database, providing a scientific basis and decision-making support for database migration, so as to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An evaluation method for a domestic database migration evaluation tool, the method comprising the following steps:

[0006] Data collection: Connect to the source database through a database connection pool to obtain the basic information of the source database, including tablespaces, database structure, table structure, constraints, indexes, data types, stored procedures, views, materialized views, functions, user-defined functions, triggers, packages, jobs, synonyms, DB-LINK; at the same time, collect the load information of the source database in a non-intrusive manner by collecting the database operation logs, including average concurrent connections, peak concurrent connections, TPS, QPS;

[0007] Source Library Analysis: Compare and analyze the information of the collected source database with the information of the alternative target domestic database, identify the differences between the two in terms of data object names, types, attributes, function definitions, and stored procedure logics. Based on the results of the difference analysis, evaluate the indicators of the database in terms of compatibility, performance, scalability, security, etc., and use algorithms and models to quantitatively evaluate the data compatibility risk, migration workload, and performance impact; among them, the data compatibility risk assessment is to compare the compatibility of data objects, data types, functions, and stored procedures between the source database and the target database, and use an expert system or a machine learning model to quantitatively evaluate the risk; the migration workload assessment is to estimate the workload in terms of business logic migration, table structure migration, data migration, and test verification based on the results of the difference analysis and the migration strategy; the performance impact prediction is to simulate the running environment of the database after migration and use benchmark testing and stress testing methods to predict the impact of migration on the database performance, including but not limited to query response time, throughput, and concurrent processing ability.

[0008] Target Library Recommendation: Based on the results of the source library analysis, comprehensively consider the migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security indicators, assign weights to each indicator, score each candidate database, calculate the comprehensive score using the weighted sum method, and select the candidate database with the highest comprehensive score as the recommended database.

[0009] Report Generation: Integrate the analysis results, migration assessment, and risk assessment of the previous steps to generate a detailed migration assessment report. The report content includes the source database profile, target database selection recommendation, migration and transformation workload, migration risks, and improvement measures.

[0010] Preferably, the data collection step also includes researching the database performance requirements of users.

[0011] Preferably, in the source library analysis step, the algorithms and models used for risk assessment include but are not limited to expert systems and machine learning models, which are used to quantitatively evaluate data compatibility risks, estimate migration workloads, and predict performance impacts.

[0012] Preferably, in the target library recommendation step, the evaluation index set includes migration complexity indicators, performance indicators, compatibility indicators, security indicators, cost indicators, scalability indicators, and maintainability indicators. Weights are assigned to each indicator, and the sum of the weights is 1, and the weights can be adjusted and optimized according to specific circumstances.

[0013] Preferably, in the report generation step, the source database profile includes the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source database. The panoramic analysis provides the association relationships and feature identification information of the objects. The target database selection recommendation includes the object compatibility and SQL compatibility of the target database version with respect to the source database, and intelligently analyzes the usage scenarios of the source database. The migration and transformation workload comprehensively considers factors such as migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security. The migration risks and improvement measures are proposed based on the previous risk assessment results.

[0014] An evaluation system for an evaluation method of a domestic database migration evaluation tool, the system comprising:

[0015] A data collection module for collecting the basic information and load information of the source database, where the basic information includes tablespaces, database structures, table structures, constraints, indexes, data types, stored procedures, views, materialized views, functions, user-defined functions, triggers, packages, jobs, synonyms, DB-LINKs, and the load information includes the average concurrent connection number, peak concurrent connection number, TPS, and QPS. This module connects through a database connection pool to obtain the basic information and non-intrusively collects the load information by collecting the database operation logs;

[0016] A source database analysis module for comparing and analyzing the collected source database information with the alternative target domestic database information, identifying the differences between the two, including comparisons in terms of data object names, types, attributes, function definitions, and stored procedure logics, evaluating the indicators of database compatibility, performance, scalability, and security, and evaluating the risks and challenges that may be encountered during the migration process based on the difference analysis results to generate a risk assessment report;

[0017] A target database recommendation module for, based on the results of the source database analysis module, comprehensively considering the migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security indicators, defining an evaluation index set, assigning weights to each index, scoring each candidate database, calculating the comprehensive score using the weighted sum method, and selecting the candidate database with the highest comprehensive score as the recommended database;

[0018] A report generation module for integrating the analysis results, migration evaluation, and risk assessment of the previous modules to generate a detailed migration evaluation report. The report content includes the source database profile, target database selection recommendation, migration and transformation workload, migration risks, and improvement measures;

[0019] A user interaction interface for interacting with the user, displaying the results of the data collection, source database analysis, target database recommendation, and report generation modules, and receiving the user's input and instructions.

[0020] Preferably, the data acquisition module further includes a research unit for researching the database performance requirements of users.

[0021] Preferably, the source database analysis module uses a series of algorithms and models to quantitatively evaluate risks, including a data compatibility risk assessment unit for evaluating compatibility risks in terms of data objects, data types, functions, and stored procedures, and quantitatively evaluating risks using an expert system or a machine learning model; a migration workload assessment unit for estimating the workload to be completed during the migration process based on the difference analysis results and migration strategies; and a performance impact prediction unit for predicting the impact of the migration on the database performance by simulating the operating environment of the database after migration.

[0022] Preferably, the target database recommendation module includes:

[0023] An evaluation index set definition unit for defining migration complexity indexes, performance indexes, compatibility indexes, security indexes, cost indexes, scalability indexes, and maintainability indexes;

[0024] A weight assignment unit for assigning weights to each index, the sum of the weights being 1, and the weights being adjustable and optimizable according to specific circumstances;

[0025] A scoring mechanism unit for scoring each candidate database according to the defined evaluation indexes;

[0026] A comprehensive score calculation unit for calculating the comprehensive score of each candidate database using the weighted sum method;

[0027] A decision output unit for selecting the candidate database with the highest comprehensive score as the recommended database.

[0028] Preferably, the migration evaluation report generated by the report generation module includes:

[0029] A source database profile, which is the result of multi-dimensional evaluation and analysis of the source database data, including the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source database, where the panoramic analysis provides the association relationships and feature identification information of the objects;

[0030] Target database selection recommendation, including the object compatibility and SQL compatibility of the target database version with the source database, intelligently analyzing the source database usage scenario, and giving the recommended target database;

[0031] The migration transformation workload, which is output by comprehensively considering migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security factors;

[0032] Migration risks and improvement measures, which are proposed based on the risk assessment results of the source database analysis module.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] The evaluation method and system of the domestic database migration evaluation tool proposed by the present invention have a high degree of automation, reduce manual intervention, and lower the complexity and error rate of evaluation; the evaluation results are multi-dimensional, covering multiple aspects such as compatibility and migration workload; it has a wide range of applications and can be applied to the migration evaluation of various domestic databases; it reduces the technical threshold of database migration evaluation, enabling non-professional technical personnel to also carry out preliminary evaluation work. Brief Description of the Drawings

[0035] Figure 1 It is a flowchart of the method of the present invention;

[0036] Figure 2 It is an architecture diagram of the system of the present invention. Detailed Embodiments

[0037] In order to clearly and completely describe the purpose and technical solutions of the present invention and make the advantages more clear, the following further details the embodiments of the present invention with reference to the drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, not to limit the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0038] Embodiment 1, please refer to Figure 1 The present invention provides a technical solution: an evaluation method of a domestic database migration evaluation tool, and the method includes the following steps:

[0039] Data collection: Connect to the source database through a database connection pool to obtain the basic information of the source database, including tablespace, database structure, table structure, constraints, indexes, data types, stored procedures, views, materialized views, functions, custom functions, triggers, packages, jobs, synonyms, DB-LINK; at the same time, collect the load information of the source database non-intrusively by collecting the database operation logs, including the average concurrent connection number, peak concurrent connection number, TPS, QPS; it also includes investigating the database performance requirements of users.

[0040] Source Library Analysis: Compare and analyze the information of the collected source database with the information of the alternative domestic target database, identify the differences between the two in terms of data object names, types, attributes, function definitions, and stored procedure logics. Based on the results of the difference analysis, evaluate the indicators of the database in terms of compatibility, performance, scalability, security, etc., and use algorithms and models to quantitatively evaluate the data compatibility risk, migration workload, and performance impact. Among them, the data compatibility risk assessment is to compare the compatibility of data objects, data types, functions, and stored procedures between the source database and the target database, and use an expert system or a machine learning model to quantitatively evaluate the risk; the migration workload assessment is to estimate the workload in terms of business logic migration, table structure migration, data migration, and test verification according to the results of the difference analysis and the migration strategy; the performance impact prediction is to simulate the operating environment of the database after migration and use benchmark testing and stress testing methods to predict the impact of migration on the database performance, including but not limited to query response time, throughput, and concurrent processing ability. The algorithms and models used for risk assessment include but are not limited to expert systems and machine learning models, which are used to quantitatively evaluate the data compatibility risk, estimate the migration workload, and predict the performance impact.

[0041] Target Library Recommendation: Based on the results of the source library analysis, comprehensively consider the migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security indicators, assign weights to each indicator, score each candidate database, calculate the comprehensive score using the weighted sum method, and select the candidate database with the highest comprehensive score as the recommended database; the evaluation index set includes migration complexity indicators, performance indicators, compatibility indicators, security indicators, cost indicators, scalability indicators, and maintainability indicators, assign weights to each indicator, the sum of the weights is 1, and the weights can be adjusted and optimized according to specific situations.

[0042] Report Generation: Integrate the analysis results, migration evaluation, and risk assessment of the previous steps to generate a detailed migration evaluation report. The report content includes the source database profile, target database selection recommendation, migration transformation workload, migration risks, and improvement measures; the source database profile includes the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source library, and the panoramic analysis provides the association relationships and feature identification information of the objects; the target database selection recommendation includes the object compatibility and SQL compatibility of the target library version with the source library, and intelligently analyzes the usage scenarios of the source library; the migration transformation workload comprehensively considers migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security factors; the migration risks and improvement measures are proposed based on the results of the previous risk assessment.

[0043] Embodiment 2, based on Embodiment 1, proposes an evaluation system, including the following modules: a data collection module, a source library analysis module, a target library recommendation module, a report generation module, and a user interface.

[0044] 1. Data collection module: responsible for collecting the basic information and load information of the source database. The basic information includes table structure, business logic, and stored data. The table structure mainly includes information such as tablespace, database structure, table structure, constraints, indexes, data types, etc.; the business logic mainly includes information such as stored procedures, views, materialized views, functions, user-defined functions, triggers, packages, jobs, synonyms, DB-LINK, etc.; the stored data mainly includes the capacity of the data, storage medium, full amount of data, and data increment situation. The load information mainly collects information such as the average concurrent connection number, peak concurrent connection number, TPS, QPS, etc. of the database.

[0045] The basic information of the database is connected through a database connection pool to obtain the actual basic information. The load information module collects data by collecting the database operation logs. There is no intrusion into the database and it will not affect the load. At the same time, it investigates the database performance requirements of users.

[0046] 2. Source database analysis module: compares and analyzes the collected source database information with the alternative target domestic database information to identify the differences between the two. The difference analysis mainly includes the comparison of data object names, types, attributes, function definitions, stored procedure logic, etc., so as to obtain the index comparison in terms of database compatibility, performance, scalability, security, etc. At the same time, it is also necessary to compare in terms of database cost, maintainability, etc.

[0047] Based on the results of the difference analysis, evaluate the possible risks and challenges during the migration process. Risk assessment includes aspects such as data compatibility risk, migration workload assessment, performance impact prediction, etc. This module uses a series of algorithms and models to quantitatively evaluate the risks and generates a risk assessment report.

[0048] (1) Data compatibility risk assessment: Based on the results of the difference analysis, evaluate the compatibility risks in aspects such as data objects, data types, functions, and stored procedures. Use an expert system or machine learning model to quantitatively evaluate the risks.

[0049] (2) Migration workload assessment: According to the results of the difference analysis and migration strategies (such as manual migration, tool-assisted migration, etc.), estimate the workload that needs to be completed during the migration process. Workload assessment includes aspects such as business logic migration, table structure migration, data migration, and test verification.

[0050] (3) Performance impact prediction: By simulating the operating environment of the database after migration, predict the impact of migration on the database performance. Performance prediction includes but is not limited to aspects such as query response time, throughput, and concurrent processing ability. Use methods such as benchmark testing and stress testing for performance evaluation.

[0051] III. Target Database Recommendation Module: Based on the results of the source database analysis module, comprehensively consider aspects such as the migration workload (complexity), compatibility, performance requirements, cost, maintainability, scalability, and security of the database, and intelligently recommend the target database.

[0052] Intelligent Recommendation Evaluation Model for Target Database:

[0053] (1) Define the evaluation index set:

[0054] Migration Complexity Index (T): Evaluate the workload, difficulty, and potential risks of data migration

[0055] Performance Index (P): Include query speed, concurrent processing ability, throughput, etc.

[0056] Compatibility Index (C): Evaluate the compatibility with the source database

[0057] Security Index (A): Security functions such as data encryption, access control, and audit logs

[0058] Cost Index (E): Purchase cost, license fee, maintenance cost, etc.

[0059] Scalability Index (S): Ability to support horizontal or vertical expansion

[0060] Maintainability Index (M): Ease of use, degree of documentation, community support, etc.

[0061] (2) Weight Assignment:

[0062] Assign a weight (W) to each index, and the sum of the weights is 1. The weight reflects the importance of the index in the decision-making process.

[0063] The recommended weights are as follows:

[0064] Migration Complexity Index (T): 25%

[0065] Performance Index (P): 20%

[0066] Compatibility Index (C): 13%

[0067] Security Index (A): 12%

[0068] Cost Index (E): 10%

[0069] Scalability Index (S): 10%

[0070] Maintainability Index (M): 10%

[0071] Note: In actual applications, the weight assignment may need to be adjusted and optimized according to specific situations.

[0072] (3) Scoring mechanism:

[0073] For each candidate database, a score (Score_i) is calculated according to the defined evaluation metrics. The scoring can be based on expert judgment, test data, or other quantitative criteria.

[0074] (4) Comprehensive score calculation:

[0075] The weighted sum method is used to calculate the comprehensive score of each candidate database. The formula is:

[0076]

[0077] where (j) represents the (j)th candidate database, (N) is the number of evaluation metrics, (Score ij ) is the score of the (i)th metric for the (j)th candidate database, and (W i ) is the weight of the (i)th metric.

[0078] (5) Decision output: Select the candidate database with the highest comprehensive score as the recommended database.

[0079] Note: Some metrics may be difficult to directly quantify the score. In this case, multiple methods such as expert scoring, questionnaire surveys, or test data can be used for evaluation. Other non - quantitative factors, such as strategic cooperation and technical route matching degree, may need to be considered during the evaluation process. These factors can be incorporated into the decision - making process by adjusting the weights or as additional conditions.

[0080] IV. Report generation module: Integrate the analysis results, migration evaluation, risk assessment, etc. of the previous steps to generate a detailed migration evaluation report. The report content includes the source database profile, target database selection recommendation, migration and transformation workload, migration risks, etc.

[0081] The source database profile is the result of multi - dimensional evaluation and analysis of the source database data, including the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source database. The panoramic analysis provides information such as the association relationships and feature identifiers of the objects; the target database selection recommendation includes the object compatibility and SQL compatibility of the target database version with respect to the source database, intelligently analyzes the source database usage scenarios, and gives the recommended target database; for the recommended target database version, considering factors such as migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security, the migration and transformation workload is output, and migration risks and improvement measures are evaluated and prompted.

[0082] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An evaluation method for a domestic database migration evaluation tool, characterized in that: The method includes the following steps: Data collection: Connect to the source database through a database connection pool to obtain the basic information of the source database, including tablespace, database structure, table structure, constraints, indexes, data types, stored procedures, views, materialized views, functions, custom functions, triggers, packages, jobs, synonyms, DB-LINK; at the same time, collect the load information of the source database non-intrusively by collecting the database operation logs, including average concurrent connection number, peak concurrent connection number, TPS, QPS; Source database analysis: Compare and analyze the collected source database information with the alternative target domestic database information, identify the differences between the two in terms of data object names, types, attributes, function definitions, and stored procedure logics, and based on the results of the difference analysis, evaluate the indicators of the database in terms of compatibility, performance, scalability, security, etc., and use algorithms and models to quantitatively evaluate the data compatibility risk, migration workload, and performance impact; among them, the data compatibility risk assessment is to compare the compatibility of data objects, data types, functions, and stored procedures between the source database and the target database, and use an expert system or a machine learning model to quantitatively evaluate the risk; the migration workload assessment is to estimate the workload in terms of business logic migration, table structure migration, data migration, and test verification according to the results of the difference analysis and the migration strategy; the performance impact prediction is to simulate the running environment of the database after migration and use benchmark testing and stress testing methods to predict the impact of migration on the database performance, including but not limited to query response time, throughput, and concurrent processing ability; Target database recommendation: Based on the results of the source database analysis, comprehensively consider the migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security indicators, assign weights to each indicator, score each candidate database, calculate the comprehensive score using the weighted sum method, and select the candidate database with the highest comprehensive score as the recommended database; Report generation: Integrate the analysis results, migration evaluation, and risk assessment of the previous steps to generate a detailed migration evaluation report. The report content includes the source database profile, target database selection recommendation, migration and transformation workload, migration risks, and improvement measures.

2. The evaluation method of a domestic database migration evaluation tool according to claim 1, characterized in that: The data collection step also includes researching the database performance requirements of users.

3. The evaluation method of a domestic database migration evaluation tool according to claim 2, characterized in that: In the source database analysis step, the algorithms and models used for risk assessment include but are not limited to expert systems and machine learning models, which are used to quantitatively evaluate the data compatibility risk, estimate the migration workload, and predict the performance impact.

4. The evaluation method of a domestic database migration evaluation tool according to claim 3, characterized in that: In the target database recommendation step, the evaluation index set includes migration complexity indicators, performance indicators, compatibility indicators, security indicators, cost indicators, scalability indicators, and maintainability indicators. Weights are assigned to each indicator, and the sum of the weights is 1, and the weights can be adjusted and optimized according to specific situations.

5. The evaluation method of a domestic database migration evaluation tool according to claim 4, characterized in that: In the report generation step, the source database profile includes the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source database. The panoramic analysis provides the association relationships and feature identification information of the objects; The target database selection recommendation includes the object compatibility and SQL compatibility of the target database version with respect to the source database, and intelligently analyzes the usage scenarios of the source database; The workload of migration and transformation comprehensively considers factors such as migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security; Migration risks and improvement measures are proposed based on the results of the previous risk assessment.

6. An evaluation system for the evaluation method of the domestic database migration evaluation tool according to claim 5, characterized in that: The system includes: A data collection module, which is used to collect the basic information and load information of the source database. The basic information includes tablespace, database structure, table structure, constraints, indexes, data types, stored procedures, views, materialized views, functions, user-defined functions, triggers, packages, jobs, synonyms, and DB-LINK. The load information includes the average concurrent connection number, peak concurrent connection number, TPS, and QPS. This module obtains the basic information through the database connection pool, and collects the load information non-intrusively by collecting the database operation logs; A source database analysis module, which is used to compare and analyze the collected source database information with the alternative target domestic database information, identify the differences between the two, including the comparison of data object names, types, attributes, function definitions, and stored procedure logics, evaluate the indicators of database compatibility, performance, scalability, and security, and evaluate the risks and challenges that may be encountered during the migration process based on the results of the difference analysis, and generate a risk assessment report; A target database recommendation module, which is used to define an evaluation index set based on the results of the source database analysis module, comprehensively consider migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security indicators, assign weights to each indicator, score each candidate database, calculate the comprehensive score using the weighted sum method, and select the candidate database with the highest comprehensive score as the recommended database; A report generation module, which is used to integrate the analysis results, migration evaluation, and risk evaluation of the previous modules, and generate a detailed migration evaluation report. The report content includes the source database profile, target database selection recommendation, migration and transformation workload, migration risks, and improvement measures; A user interface, which is used to interact with the user, display the results of the data collection, source database analysis, target database recommendation, and report generation modules, and receive the user's input and instructions.

7. An evaluation system according to claim 6, characterized in that: The data collection module also includes a research unit, which is used to research the user's database performance requirements.

8. An evaluation system according to claim 7, characterized in that: The source database analysis module uses a series of algorithms and models to quantitatively evaluate risks, including a data compatibility risk assessment unit, which is used to evaluate the compatibility risks in terms of data objects, data types, functions, and stored procedures, and quantitatively evaluate the risks using an expert system or a machine learning model; A migration workload assessment unit, which is used to estimate the workload that needs to be completed during the migration process based on the results of the difference analysis and the migration strategy; a performance impact prediction unit, which is used to predict the impact of the migration on the database performance by simulating the running environment of the database after migration.

9. An evaluation system according to claim 8, characterized in that: The target database recommendation module includes: An evaluation index set definition unit, which is used to define migration complexity indicators, performance indicators, compatibility indicators, security indicators, cost indicators, scalability indicators, and maintainability indicators; A weight assignment unit, which is used to assign weights to each indicator. The sum of the weights is 1, and the weights can be adjusted and optimized according to the specific situation; A scoring mechanism unit for scoring each candidate database according to the defined evaluation metrics; A comprehensive score calculation unit for calculating the comprehensive score of each candidate database using the weighted sum method; A decision output unit for selecting the candidate database with the highest comprehensive score as the recommended database.

10. An evaluation system according to claim 6, characterized in that: The migration evaluation report generated by the report generation module includes: The source database profile, which is the result of multi-dimensional evaluation and analysis of the source database data, including the performance, capacity, characteristics, external dependencies, object details, and panoramic search of the source database. The panoramic analysis provides the association relationships and feature identification information of the objects; The target database selection recommendation, which includes the object compatibility and SQL compatibility of the target database version with the source database, intelligently analyzes the usage scenarios of the source database, and gives the recommended target database; The workload of migration and transformation, which is output by comprehensively considering factors such as migration complexity, compatibility, performance requirements, cost, maintainability, scalability, and security; The migration risks and improvement measures, which are proposed based on the risk assessment results of the source database analysis module.

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