19 Sep 2017

WANdisco Launches One of the First Hybrid Data Lake Architectures in Collaboration with AWS

San Ramon, CA – WANdisco, a world leader in Active Data Replication^®, today announced the launch of one of the first hybrid data lake architectures in collaboration with Amazon Web Services (AWS). Using patented WANdisco Fusion^® technology, continuously changing data from AWS on-premises data lakes can now be replicated to and from AWS with guaranteed consistency, no downtime, and no business disruption.

The integration of on-premises Hadoop clusters with the data lake solution on AWS, WANdisco Fusion^® and Amazon Simple Storage Service (Amazon S3) in one of the industry’s first hybrid data lake architectures supports use cases such as seamless disaster recovery in the event of an outage and cloud migration to unlock the full potential of cloud analytics for disruptive business intelligence – all whilst lowering overheads. Data that has been replicated to Amazon S3 can also be used by Amazon Athena to provide capacity as required for burst out processing for ad-hoc queries of unstructured, semi-structured, and structured data sets. 

David Richards, CEO and Co-founder of WANdisco said:

“The integration of WANdisco Fusion as part of one of the first hybrid data lake architectures shows we are a critical part of the cloud and on-premises ecosystems. This enterprise-grade solution moves active, continuously changing data to the cloud with no downtime and no disruption, keeping both on-premises and cloud environments in sync. With the  data lake solution on AWS, enterprises can benefit from real-time analytics from multiple sources, enabling them to accelerate product and service innovation, improve customer experience and respond to current and future regulatory and compliance requirements.” 

To access the Quick Start Reference Deployment Guide “Hybrid Data Lake on AWS” please click here.

For further information please contact:

Alexandra Gee, VP Marketing & Communications          Alexandra.gee@wandisco.com