Database conversion is not a trivial task. Many healthcare data migration projects involve moving millions of rows of data from one database to another. For instance, MySQL DB conversion to MS SQL or Oracle can take days, weeks, or months depending on the volume of data, the number of custom database objects, and the amount of transformation required to fit into the new database.
To automate your database conversion, you need a high-performance, user-friendly, and scalable solution. Here are some things to consider while selecting your MySQL DB conversion tool.
1. Native Support for Database Servers and Data Sources
The database conversion tool needs to query the source database (MySQL) directly. Without direct access to the database system catalogs, the converter may not accurately create the schema for the target database.
That is why your tool must have native support for the source and target database engine. Using a native database engine will improve the database schema’s quality and reduce manual adjustments required.
2. Capacity to Detect Potential Errors/ Handle Database Incompatibilities
Every database management system has features that will not convert automatically. For instance, data types, data sizes, foreign/primary key constraints, indexes, stored procedures, blobs, and image storage, can lead to incomplete conversion or conversion errors.
A well-designed conversion tool will inspect the database schema and data values carefully to detect any potential source of error. These errors should be listed in a log file, which will serve as a planning tool for the manual modifications you will do after the tool has completed schema creation.
3. Well Defined Modules and Tasks
A database conversion project involves various phases, from planning to the final deployment of the new database. Your conversion tool should be flexible enough to allow you to perform different stages of the project in installments.
You should not be forced to follow the same sequence for every project. For instance, you should inspect the source database, detect potential issues, and then come back later to create a database schema from it.
4. Management of Bulk Data Loading
Bulk data loading is a critical part of data conversion and migration. If you have an existing database with millions or billions of rows, you need a tool to load data in batches without performance issues on the database server and network.
You should run the bulk data loading into flat files on the server and then transfer the data in the files in batches using any application.
5. Effective Database Mapping
Database engines have different internal formats for storing data types. So you may need to change from one data type to another or increase the width or size of a particular data type during conversion.
A good tool will allow you to map a different data type using a common rule. For instance, you can set a rule that all nCHAR in the source database should be converted to VARCHAR(n) in the target database.
Choosing the right tools for your database conversion can improve performance and reduce the cost and time to complete the project. It can also help detect data integrity errors that can cause serious problems when the new database goes live.
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