Comprehensive real-time data replication. Simplified.

A subscription includes everything you need for efficient data replication and integration, whether you need to move your data between databases, to the cloud or multi-cloud environment, into a data lake or data warehouse.



Low-impact data movement even at high volumes with Log-Based Change Data Capture (CDC) and compression. Fast data benefits with analytics tools, a stellar customer service team, and more.


The most efficient way to replicate and integrate data in hybrid and complex environments is with HVR’s distributed, flexible and modular architecture. Design your integration flow the way you need it and stream data from one source to many, all at once, without needing to define your setup multiple times.


HVR understands the importance of data security. HVR is the only real-time data replication solution that enables routing through a firewall proxy in hybrid environments. Data is also encrypted for an added layer of protection.

With the combination of flexibility, performance and robustness, HVR has proven to be a very good choice to embed in our flight planning system.
– Senior Database Software Architect, Lufthansa

Key features. What you get with an HVR subscription:


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 Validation and Compare

Have assurance your data is accurate. Compare data before consumption. Live Compare capabilities allows for compare on data in-flight.


Insights: Statistics, and more

This tool gives you the ability to view how data is moving in real-time, be proactive and identify chokepoints.

Broad source and target support

Whether you’re replicating your data to a data lake or data warehouse, from on-prem to the cloud, we support it.

  • All
  • Source
  • Target
Amazon Redshift
Amazon RDS
Amazon Aurora on PostgreSQL
Amazon S3
Amazon Aurora on MySQL
Snowflake on AWS
Snowflake on Azure
Apache Kafka
Apache Hive
Apache HBase
Apache Cassandra
Microsoft SQL Server
Microsoft Azure SQL Database
Microsoft Azure Data Warehouse
Microsoft Azure DLS
Microsoft Azure Blob Storage
IBM DB2 on z/OS
IBM DB2 iSeries (AS400)
Google BigQuery
Actian Vector
HVR Agent Plug-in

Don’t see your platform?

Please contact us to learn more about our API agent plug-in. This plug-in gives you the ability to connect to a target not listed.


HVR has proven its stability and robustness. It keeps on running and running with minimal maintenance effort. HVR guarantees secure delivery of all our data.
– Director of IT, PostNL

A flexible, distributed architecture with a central point of control

Through HVR’s distributed architecture, you get the ability to not only move data from one source system to another but also the ability to move data bi-directionally and multi-directionally while maintaining efficiency and accuracy. All from one central console. Watch the video to see how HVR solves for use cases such as migrations, active/active, data lake consolidation, real-time reporting and more.

Features such as collision detection, data validation, and reporting and monitoring give you assurance in moving high volumes of data in your complex environments.

Topologies supported


Real-Time Reporting Migrations

(Reverse Post Migration)


Data Distribution


Active / Active Standby

High Availability

Integration / Consolidation

Data Warehouse / Data Lake


Multi-Way Active / Active

Geographical Distribution


Data Marts


Can HVR replicate data from a single source to multiple targets?
Yes, in fact that is one of the advantages of HVR’s architecture. HVR can capture from a single Oracle instance, queue the captured changes on the hub, and then integrate those changes to as many targets as needed. HVR does not have any limitation on the number of targets.

Can HVR replicate data from a multiple source to a single target?
Yes, HVR can be configured to capture data from many sources and then replicate to a single target. Many data warehousing solutions require data to be collected from any number of sources to be either combined into a single target warehouse database or into separate target schemas. Some applications and data are designed so that there will not be any conflicts on primary key constraints. If that is not the case for your scenario, then HVR offers you the option to add extra columns and set to values stored in the metadata to make sure you don’t have any conflicting primary keys.

Does my source and target layouts need to have the same structure and layout?
No, tables do not need to have the same layout. You can instruct HVR to ignore certain columns or populate extra columns during replication. Column values can also be changed through transformations as well as enriched with the results querying other tables, either on the source or the target. HVR also makes additional transactional metadata values to be available to be mapped to columns, such as source timestamps or transaction identifiers.

To minimize any impact to our network, can we compress the change data before it sent over the network?
Yes, in fact HVR already compresses the database by default before sending over the network using an internal algorithm which achieves very high compression rates. The impressive compression ratio reduces impact on your corporate network while using little overhead on the source.

When instantiating the target database, does the user have to pre-create the target tables, or can HVR help with that?
The initial load of the target tables takes place by running an HVR Refresh operation. The Refresh can create all the target tables if they don’t already exists. The target tables are created based on the DDL of the source tables in conjunction with any column re-mapping that the user has configured in the replication channel.

Can HVR convert all insert, update, and delete operations and insert them into a time-based journal or history table?
Yes, HVR Integrate provides a feature known as TimeKey which converts all changes (inserts, updates, and deletes) into inserts into separate tables. HVR will log both the before and after image for update operations, the after image for insert operations, and the before image for delete operations. HVR also logs additional transaction metadata to provide more time based details for every row replicated. HVR will also automatically create the tables with the preferred structure for timekey integration.

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