Following the modern trends,many organizations are strugglingto shift from commercial software to open-source alternatives, and so their IT departments often encounter the task of database conversion. Database conversion involves transforming data, meta-objects, stored procedures, functions, and triggers from one database management system (DBMS) format to another. This process frequently entails making changes to the application layer, mapping data types, and adjusting SQL statements.
This routine is quite complex and requires much time and efforts and it is also supplied with risk of data loss or corruption due to human errors. It is reasonable to use database conversion tools to save a lot of resources and eliminate risks of database damage.
The most valuable reasons for database conversion include:
- Reducing total ownership cost.Proprietary database management systems (DBMS) typically involve significant license fees and strict licensing terms. Conversely, open-source DBMS alternatives provide comparable functionalities and are freely available for installation and use.
- High level of customization.Open-source DBMSs generally offer a diverse selection of extensions and add-ons that enable flexible implementation of database management and development tasks. These extensions are often freely available, providing additional functionalities to enhance the capabilities of the DBMS.
Databaseconversion between two different database management systems is a challenging and time-consuming task sue to different set of supporting data types and SQL syntax. Proper database conversion tools can simplify particular stages of the process:
- In this phase, the focus is on assessing the compatibility of the systems, examining the architecture, and thoroughly reviewing the application code to identify any necessary modifications.
- Converting schemas and meta-objects.During this phase, the migration process centers around transferring the database schemas and associated meta-objects, such as tables, views, indexes, and constraints, to the target DBMS.
- Functional and performance testing.After the completion of schema migration, it becomes crucial to conduct comprehensive testing to verify the correct functioning of the migrated database and ensure it meets the necessary performance standards.
- Data Conversion.This phase involves the actual transfer of data from the source database to the target database. It includes tasks such as converting data types, managing data transformations, and ensuring data integrity throughout the entire process.
Converting schemas and meta-objects
The goal of this phase is to convert table definitions, constraints, indexes, and relationships between tables from the source DBMS format to the target. All database meta-objects must be validated to recognizeif any translation isrequired. As the result of this procedure, migration statements to create or modify the meta-object definitions are generatedin the target database.
To ensure accuracy and prevent data loss or inconsistencies, it is crucial to thoroughly test the migration scripts on a development or staging environment. This testing phase confirms that the migration scripts accurately reflect the desired table definitions. Once the migration scripts have been successfully tested, they are executed on the target database, creating the necessary table definitions, constraints, indexes, and relationships between tables.
Upon completion of the migration, a verification process is conducted to ensure that all table definitions and associated meta-objects in the target environment match the desired structure and meet the application requirements.
Database conversion tools available in the market offer various approaches and methods. These methods can be categorized into three primary categories: snapshot, parallel snapshot, and change data replication (CDR).
The snapshot method createsa single-operationsnapshot of each table being migrated and then replicate it to the destination database.During the snapshot generation, writingin the source database is prohibited. This method can impose a significant load on the source DBMS due to bulk data reading.
The parallel snapshot method is similar to the previous one except it divides the source data into fragments, then takes snapshots of these fragments and replicates them to the target database simultaneously. This method helps reduce the duration of the snapshot and the required downtime for the database conversion procedure. However, some downtime is still necessary with this method.
Another method used in database conversion tools is change data replication (CDR). This method involves monitoring and recording real-time changes from the source database and applying those changes to the target database. There are trigger-based and transaction log techniques mostly used for CDR.
The trigger-based technique modifies the source database by adding triggers on insert/update/delete that capture all the changes for each table being replicated.Then trigger-based CDR toolreplicated those changes to the target database. On the other hand, the transaction log approach relies on the undocumented and changeable format of the transaction log, which can pose compatibility risks with different versions of DBMS.
Unlike the two snapshot methods, CDR approaches may reduce the overhead on the source DBMS by capturing and applying only the changes instead of reading and transferring bulk data.
Database conversion is a intricate process that encompasses the transfer of data, meta-objects, stored procedures, functions, and triggers from one DBMS to another. Prior to executing the conversion, specialists responsible for the task must evaluate the compatibility of the application layer with the target database management system. They need to investigate disparities in schema, data formatting, and SQL dialects between the source and target DBMS, as well as conduct performance testing.
There are various methods available for implementing database conversion, each with its own advantages and disadvantages. Two commonly utilized methods are snapshot and parallel snapshot, both of them require a systemdowntime. An alternative approach to database conversion is change data replication (CDR), which enables real-time tracking and capturing of changes. CDR can be implemented through trigger-based or transaction log techniques. It is important to note that these methods may require modifications to the source database or rely on the undocumented and changeable format of the transaction log.
To ensure a successful migration project, it’s crucial to carefully choose the appropriate database conversion tools based on the specific project needs. After database conversion is properlyimplemented,organization can take advantagesof cost savings, customization, and increased flexibility of the new DBMS.