Data synchronization method between heterogeneous database systems

Abstract

The invention relates to a data synchronization method between heterogeneous database systems. The method comprises the following steps: planning a synchronization demand; configuring a synchronization parameter table based on the synchronization demand; defining dependency relationships and synchronization frequencies between the synchronization data tables and between the synchronization data tables and other modules; and calling a synchronization operation program, and performing data synchronization operation based on the configuration of the synchronization parameter table. Compared with the prior art, the method provided by the invention is high in data synchronization efficiency and high in flexibility, and can quickly position and solve problems when data synchronization is abnormal.

Description

Technical field [0001] The present invention relates to a database data synchronization technique, in particular to a heterogeneous database system data synchronization method. Background [0002] Data synchronization refers to techniques that enable data consistency between two data sources or partially on demand. Data synchronization can be applied to a variety of business scenarios, such as data remote disaster recovery, local data disaster recovery, cross-system data synchronization, cross-module data synchronization, and data consistency before and after data warehouses. [0003] At present, the data synchronization between the same database is relatively simple, such as data synchronization between Oracle databases, which can use DBLINK, imp / emp technology, expdp / impdp data pump technology and Sqluldr2 technology; DBLINK technology is usually used between Gbase databases. [0004] With the generalization of the separation of front-end and back-end databases in application s...

AI Technical Summary

Problems solved by technology

[0006] 1. The entire operation process requires manual intervention

It is necessary to clarify the difference between the source database system and the target database, the scope of the data table, and the statement difference for export and import, and then perform the export, generate the file, and execute the import. The whole process is complicated and inefficient, and there are too many manual steps

[0007] 2. It cannot meet the data synchronization requirements in multi-business scenarios

[0012] 1. The export and import process involves different databases, the whole process requires too many manual interventions, and the export and import error rate is high

[0013] 2. It cannot meet the flexible configuration requirements for the data size, synchronization frequency, synchronization method, and incremental synchronization mechanism of the synchronization data table

[0014] 3. It is not convenient and flexible to realize two-way synchronization between heterogeneous databases. For example, the DBLINK of Gbase database can only realize the synchronization from Oracle to Gbase database, but cannot realize the synchronization requirements from Gbase database to Oracle database

[0015] 4. DBLINK and Kettle can only realize the synchronization of a small amount of data. When the amount of data reaches more than 100,000 levels, the synchronization efficiency will drop significantly

[0016] 5. For frequent data synchronization, there is no planned and standardized synchronization framework

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