Datometry, the pioneer in database virtualization, announced the availability of Datometry Hyper-Q for Databricks on the Amazon Web Services (AWS) cloud platform. The new product offering empowers enterprise customers to overcome the lock-in of legacy vendors and move business-critical workloads to Databricks rapidly.
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Enterprises struggle to move their workloads off of legacy data warehouses from vendors like Teradata and Oracle. Until now, the only way to move applications from these legacy systems was to rewrite application code and translate the embedded SQL with conversion tools. That approach is costly, time-consuming, and extremely error-prone. The analyst firm Gartner puts the success rate of these migrations at only 20%, emphasizing the risks enterprises are bound to take.
Datometry Hyper-Q for Databricks makes existing applications work as-is with Databricks without the need to rewrite or modify them. Today, Datometry made its flagship product Hyper-Q for Databricks also available on AWS. Customers, including those using Teradata Vantage on AWS and Oracle RDS, can now run their workloads directly on Databricks in AWS.
Datometry Hyper-Q changes the economics of database migrations fundamentally. Firstly, it eliminates the risks associated with conventional migrations. Secondly, it reduces the time-to-value from years to months and completes migrations 5x—10x faster. And lastly, customers realize cost savings of at least 70% compared to conventional migrations.
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“Adding support for Databricks on AWS was important for us as we strive to make modern data technology available everywhere,” said Mike Waas, CEO of Datometry. “This offer addresses customers who moved initially to a legacy vendor’s offering on AWS but have come to realize that they cannot sustain the high cost of these offerings long term.”
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