How to Migrate Database into Cloud

Database migration to “software as a service” (SAAS) platforms also known as cloud has become a long-term trend in IT world. The advantages that lead to growing popularity of this model are reduced TCO (total cost of ownership), scalability of hardware and software architectures, virtualization of data.

Most vendors of popular DBMS also offer SAAS platforms, for example: 

• SQL Azure – cloud service for Microsoft SQL databases
• Oracle Cloud – “Database as a Service” solutions for Oracle databases
• Google Cloud SQL – web service to create, configure and use relational databases based on MySQL engine
• IBM SmartCloud – IBM cloud service for DB2 databases
• Amazon Relational Database Service (RDS) – cloud services for IBM DB, MySQL, Microsoft SQL and Oracle databases by Amazon

 Database migration to SAAS platform consists of the following steps.

1. Plan and setup. Main goal of this phase is to recognize all features that are not supported in the target DBMS and the necessary application changes caused by migration. 

This step demands for a lot of human resources because it is about understanding database applications semantic. Although some database administration tools that can compare two database systems and identify missing features in the destination DBMS, the project manager must understand the role of those features and find design alternatives. The advantages of database migration are compared to development efforts and cost of deploying the alternatives. The results of that analysis lead to final decision about database migration instead of using missing features as reason to not migrate to the cloud at all. 

1. Development. On this step database developers should implement tasks generated on the previous phase. Most databases migration projects include some application changes. Even migration from database server to SAAS platform of the same DBMS usually deals with minor differences between source and destination systems. For example, SQL Server database migrated to Azure SQL requires clustered indexes for each table that does not have it. Also, database developer must remember that Azure SQL does not support RESTORE statement and cannot attach databases to the SQL server. 

The architecture of application layer may require modifications even if no database objects were changed due to different error handling, security and logging mechanism used in source and destination DBMS. 

1. Test. Many database specialists consider it as the most important phase of the entire migration process. It is far less risky to validate the project regularly and fix all diagnosed problems than having unreviewed code for long periods. 

Here are the areas of primary attention for both developers and planers within testing phase: 

• Security system
• Error handling
• Logging
• Retry logic
• Network issues
• Scale-out concept

It is greatly recommended to isolate the database during test phase, otherwise results of benchmarking may be wrong. 

Intelligent Converters Solutions 

Intelligent Converters software company provides a range of tools and services to migrate data from any sources (MySQL, MS Access, Oracle, Postgres, DBase/FoxPro, MS Excel, Microsoft SQL, IBM DB2) into private or public cloud. Our products work with all popular cloud-based services: SQL Azure, Oracle Cloud, Google Cloud SQL and Amazon Relational Database Service. Each converter migrates the data, constraints, indexes and queries (views) from database server to SAAS platform handling carefully all required transformations. 

This combination of high performance migration tools and cutting-edge skils allows Intelligent Converters to provide unique solutions that have helped hundreds of customers to migrate databases to both private and public clouds.