HDFS is the primary data storage system used by Hadoop applications.
Files can be captured and copied or moved to a different location. CSV and XML files can be processed for a table target. As a target, HVR can write files in multiple formats including Parquet, JSON, Avro, CSV or XML with many options to fine tune the format and define compression. Compare is supported through Hive external tables, or directly by reading/parsing the files.
 | Key Features: See how change data capture, data validation and repair, and reporting all in one tool simplify data integration management. |
 | Table Creation and Initial Load. Mapping data between source and target is automated and made easy. |
 | Log-based Change Data Capture. Only the changes are moved between source and target, a low impact way to move data. |
 | Data Compare. Have assurance your data is accurate. HVR includes the ability to compare data before consumption. |
 | Insights: This tool gives you the ability to view how data is moving in real-time, be proactive and identify chokepoints. |
In this report, Gartner analyzed and synthesized 198 Peer Insights from data and analytics leaders to identify lessons learned implementing data integration tools. The recommendations shared by your peers are complemented with expert research to provide you with valuable insight into ...
HVR Agent as a Service for Azure A key promise of the cloud is less mundane software management. Contrast the cloud to the on-premises world, with system operators, network administrators, DBAs, application administrators, etc. The Agent as a service for ...
Whether you’re moving your data to a data lake or data warehouse, from on-prem to the cloud, we support it.
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