Simplicity that delivers cost-effective performance
Big data storage is a growing concern for many companies. The ability to make informed decisions from large datasets is critical for today’s enterprises.
Data sources for analysis include mobile phones, sensors and wearable devices, as well as applications and infrastructure in the data center and the cloud.
Adequate storage is a pressing problem for data analytics. Qumulo can help.
- How should storage be attached to the compute resources to ensure high availability of data with low latency and horizontal scalability
- What are the requirements for a file storage system to serve these demanding workloads?
- What are the best strategies for scaling storage over time?
Qumulo for Big Data and Analytics
Qumulo’s software is a modern file storage system that has the performance, scalability and enterprise features required by data analytic workloads.
Get your results faster
Qumulo has better sustained read throughput than direct-attached storage for analytic workloads. The performance edge of Qumulo comes from its hybrid SSD/HDD architecture and its advanced distributed file system technology.
Eliminate data silos
Qumulo provides you with a single namespace for all your data. A single repository eliminates multiple copies of data and simplifies your workflow.
Run in the cloud and on premises
Continuous replication means you can easily transfer data from your on-premise Qumulo cluster to your Qumulo cluster in AWS, perform their computations, and then transfer the results back to the on-premise storage.
Buy only the storage you need
With Qumulo, customers have control over how much storage they buy and can avoid overprovisioning. With Qumulo, you save money by buying only the storage you need, regardless of how your compute cluster grows.
Solve storage problems in real time
Qumulo lets administrators find and solve problems in real time. It’s easy to manage your projects and users when you have insight into how the storage is being used.
How it Works
Data Analytics Workflow
Here is an example of a streaming data analytics workflow that shows Qumulo as the central, storage for the entire process, from ingesting the data to displaying it and acting on it.
Input can come from devices, such as cell phones, scientific instruments, autonomous vehicles and serial devices. It can also come from applications, which typically store their data in Qumulo’s file system and then send a link to the event data flow software packages. The compute resources process the data and both store and retrieve files from Qumulo. Finally, the results are delivered and either displayed as information on a dashboard or used to trigger a particular action, such as a security alert.