VMware vSphere® Big Data Extensions (BDE) simplifies running Big Data workloads on the vSphere platform to deliver a new level of efficiency and agility.

Achieve Operational Simplicity with Performance

Automated deployment and management of Hadoop clusters

  • Use vCenter to install and configure clusters
  • BDE clones VMs from a template and controls/configures VMs through vCenter
  • Deploy clusters with HDFS, MapReduce, HBase, Pig, Hive and Hive Server

Virtualization of multiple Hadoop distributions

  • Use BDE in conjunction with multiple Hadoop distributions: Apache Hadoop, Cloudera, Pivotal, Hortonworks, and MapR

No degradation in Performance

  • Performance benchmark testing shows on par performance when compared to physical deployments depending on configuration
Deploy Hadoop Clusters in Minutes graphic

Deploy Hadoop Clusters in Minutes

Maximize Resource Utilization on New or Existing Hardware

Elastic scaling

  • Deploy separate compute clusters for different tenants sharing HDFS
  • Commission/decommission compute nodes according to priority and available resources

True Multi-tenancy

  • Separating data from compute allows for seamless scaling of the compute layer while keeping data persistent and safe
  • Users can run mixed workloads simultaneously on a single physical host

VM-based Isolation

  • Ensure you have reserve resources to meet your needs and run concurrent applications or Hadoop distributions
  • Provide privacy and data isolation between multiple users of your Hadoop cluster
Elastic scaling

Elastic scaling

Architect Scalable and Flexible Big Data Platform for the Enterprise

Hadoop virtualization that can leverage local, shared, or hybrid storage architecture

  • BDE supports local storage and shared storage options such as Isilon NAS
  • Scalable storage bandwidth to lower cost/GB

High Availability

  • One-click failover protection against hardware and operating system failures will allow your Hadoop jobs to restart where they left off

Fully customizable configuration profile

  • Dedicated machines or share with other workload
  • Shared or local storage
  • Static IP or DHCP network
  • Fully control the placement of Hadoop nodes