Our data validation feature tells you whether your data is in sync and alerts you if there’s a problem.
This validation feature supports many relational database management systems. When data types are compatible, the differences are managed automatically. You can also manually specify transactions to easily compare incompatible data types, differing data structures, and alternative naming.
Know that the data you are delivering to your teams is not only on time but accurate. They can feel confident they are making business decisions on the right information.
No need to spend countless hours trying to identify errors and re-run integration jobs. Find and fix errors in minutes.
When data is in sync, you can spend more time focusing on optimizing data flows and other priority workloads.
Data validation is taken to the next level of measuring data accuracy with our Live Compare feature:
1. Live Compare: Merge the changes in the HVR transaction files with any detected differences based on selecting the data from either side of the data flow. You can then give an exact answer on whether two systems are in sync, irrespective of in-flight changes.
2. Live Compare using a two-pass approach: Used to validate if databases are in sync or not, regardless if they are being replicated with HVR or any other replication tool.
3. File Compare: Perform a direct reading of the files instead of relying on Hive external tables to retrieve the data. This new approach no longer requires implicit data rounding and truncation as part of coercion and is more scalable than the existing approach using Hive. This also saves the cost of running Hive in the cloud.
How do you make sure your data is bit correct in the source and target systems? In this video, learn how the Big Data Compare feature in HVR enables you to make sure your data is correct and in sync. VP of Field Engineering, Joe deBuzna, explains how the Big Data Compare function works in HVR, why it is important for your business, and how it can identify and mitigate errors.