Optimize your schema
Convert the existing schema of your legacy data warehouse and lay the foundation in the cloud. qShift takes into account all existing objects in the source data warehouse schema and generates optimized DDL for the destination data warehouse. With SmartSchema™, qShift addresses even the most advanced concepts reaching over 99.5% fidelity on average.
Lay the right foundation
Datometry SmartSchema is a sophisticated semantic layer that bridges the fundamental differences between source and destination schema. It combines the best of both worlds: use the new schema natively in new developments while existing applications view the same data through the lens of the legacy schema.
No two data warehouses have the same type system. SmartSchema emulates advanced data types such as intervals or time formats so applications need not to be rewritten
Control flow features such as Stored Procs or Macros may have very different semantics — or may not exist at all in the destination cloud data warehouse. SmartSchema emulates these semantics seamlessly.
Updatable Views or Global Temporary Tables are but two of the many operational features in legacy schemas. With SmartSchema this functionality becomes available on cloud data warehouses.
Frequently Asked Questions
See also for answers to more frequently asked questions.
Datometry qShift transforms the original source schema into a SmartSchema™ on the destination system. SmartSchema™ can represent additional data and object types that do not natively exist on the destination system and optimize for performance and completeness.
Currently, Datometry qShift supports Azure Synapse, Amazon Redshift, and Google BigQuery.
Datometry qShift takes best practices for the destination data warehouse into account and combines it with the unique knowledge and experience of Datometry in their analysis of production workloads. Datometry optimizes and improves the output of qShift constantly in close collaboration with our cloud data warehouse partners.