Easy Database Migration with Data Virtualization

| January 3, 2019

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Some still see data virtualization as an alternative technology to ETL. For them it’s nothing more than another style of data integration. However, data virtualization is much more. Data virtualization is about abstraction. It’s about data consumers being decoupled from the data stores and data producers. It’s about being able to develop applications that are not tied directly to a specific database technology. And it’s this capability that makes it valuable for all kinds of use cases, and one of them is database migration.In recent years, many powerful, scalable, and fast new database platforms have been released, such as the Hadoop patform; some of the NoSQL products; the analytical SQL products, such as SnowflakeDB, Google BigQuery, Amazon RedShift, and memSQL; the GPU-based databases, such as Kinetica and MapD; and the list goes on. To exploit this new technology, a migration is required. The need for migration may come from the desire to switch to a cheaper platform, or to a faster and more scalable platform, or to move data to the cloud and run a platform designed and optimized for the cloud.

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