Decrease costs and accelerate results. Easily.
Lower the cost of data analytics:
- Reduce compute idle time caused by I/O.
- Take advantage of smaller servers and lower run-time costs.
- Eliminate unpredictable costs associated with object storage.
- Minimize complexity—eliminate the burden of planning for object storage layouts.
Improve analytics speeds and boost cloud storage performance with up to 30 times faster I/O than competing file services.
Bring your file-based application data closer to cloud-based analytics services.
- Increase analytics performance in the cloud with Microsoft Azure HDInsight on Azure NetApp® Files.
- Build your own Hadoop infrastructure in the cloud with Hortonworks on Amazon Web Services (AWS) and Google Cloud Platform (GCP).
- Simplify GCP deployments with Cloud Dataproc integration and the NetApp Cloud Volumes Service API.
- Optimize AI workload deployments: Get integrated Nvidia graphics processing unit (GPU) support on AWS and Azure. Get tensor processing unit (TPU) as a service on GCP.
Increase user productivity.
- Capitalize on the value of your data by empowering more users and applications on the same dataset.
- Perform data access and in-place analytics at the same time.
- Easily copy data to address requirements outside the standard workflow, such as audits.
Create a Challenge-Free Repository for Data Analytics Workloads
This white paper examines how to facilitate analytics in the cloud to synchronize data from multiple data sources, gather data from compute clusters, and provision data test environments.
The Global Platform for Genomic Data: WuXi NextCODE
- Three times faster than self-managed block storage
- Accelerated performance: previously impossible calculations reduced to 45 minutes using NetApp Cloud Volumes Service
- Easy onboarding: 30TB >2M files up in ˂2 days