Such transformations are anything but trivial and, unfortunately, often not sustainably costly. This is mainly because data, the lifeblood of any organization today, is stored in many different types of databases, applications, and systems, and many organizations simply cannot afford to disrupt data access while building and implementing new infrastructure. Even when companies try to install a new system alongside an existing legacy system such as a data warehouse, it is difficult to integrate the data between the old and new systems to support today’s demanding use cases.

Most data integration solutions rely on the physical replication of data to a new repository using ETL (Extract, Transform and Load) processes. However, these processes are stack-oriented so they cannot support real-time data access, which is becoming more and more important. Additionally, they don’t support agility as they have to be rewritten, retested, and redeployed every time …

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