Nutanix Big Data
High performance for virtualized big data installations
Predictable performance, linear scaling and high availability
Big data applications like Splunk, Cloudera, NoSQL, Hadoop and others are pushing the performance and scalability limits of traditional infrastructures, requiring good sequential and random performance across large datasets and multiple nodes. Nutanix delivers performance equivalent to bare metal deployments while significantly simplifying infrastructure management from your virtualized big data installations.
- Splunk
Simplified Operations
Streamline infrastructure and storage management tasks, and leverage standard virtual machine management.
Easy Management
Simple to use Prism delivers single pane management for the entire server and storage infrastructure.
Simple to use Prism delivers single pane management for the entire server and storage infrastructure.
Efficient Use of Infrastructure
Hadoop and Splunk deployments can coexist with enterprise applications in the same environment using sandbox workloads.
Hadoop and Splunk deployments can coexist with enterprise applications in the same environment using sandbox workloads.
Fast Time-to-value
Nutanix and big data applications like Splunk and Hadoop can be up and running in just a few hours.
Nutanix and big data applications like Splunk and Hadoop can be up and running in just a few hours.
Fast, Efficient Performance
Deliver up to 3x performance in only 25% of the space needed for 3-tier solutions, accommodating 100,000s of events/second.
Quick Search and Index
Delivers 2-3x greater events/sec for each appliance than competing solutions for mission-critical applications.
Delivers 2-3x greater events/sec for each appliance than competing solutions for mission-critical applications.
Linear Scaling
Start small and scale up one node at a time with access to over 1TB of data ingest/day.
Start small and scale up one node at a time with access to over 1TB of data ingest/day.
Reduced Footprint
Hyperscale architecture and optimizations such as deduplication and compression reduce hardware footprints by up to 4x.
Hyperscale architecture and optimizations such as deduplication and compression reduce hardware footprints by up to 4x.