The biggest challenge with big data is, well, it's big. Generating the data isn't the problem. These days, there's a steady flow of data coming from all around: enterprise systems that process transactions, web-based systems that track customer clicks, Internet of Things devices that capture a sensor measurement every millisecond, customer comments on Facebook, Twitter, user forums,…data is everywhere.
Challenges of Scale for Storage and Compute
There's value in that data, which is why it's worth preserving. But what do you do with that onrush of data? The volume only increases; big data needs all those historical values, so there's no longer obsolete data that can be discarded to free up space. Keeping it means your storage space just grows, and grows, and grows. That constantly growing footprint, and the challenge of scaling storage, leads many companies to look to the cloud to store their big data.
Security concerns about cloud storage make this an uncomfortable choice for some businesses. This data contains the insights that companies hope will guide the direction of their business; they would prefer to retain full control over such valuable data.
Once you've figured out the storage solution, there are more challenges in making use of the data. How do you fit the servers needed to process all that data into your data center? The most popular tool for big data analyses, Hadoop, relies on a scalable cluster of servers, with calculation tasks happening close to the data. That means businesses need to build a large suite of servers, which will mostly be idle most of the time. Even with Hadoop's ability to use commodity servers, that can be a significant cost.
Hyperconverged Infrastructure Meets Big Data's Needs
Hyperconverged infrastructure like Nutanix can help companies solve the challenge of fitting big data into their data centers with a smaller footprint. By design, hyperconverged infrastructure treats storage and compute as a single unit, and it's designed to scale by simply adding nodes. This is exactly the demand that comes with Hadoop and big data.
By using virtualization, the hyperconverged infrastructure can support both enterprise processing and big data analytics, increasing the utilization of the servers and making the calculations cost effective. High availability built into the hyperconverged infrastructure provides redundancy that backs up the Hadoop NameNodes. While Hadoop services typically require the Hadoop Distributed File System, and Nutanix will support it, Nutanix also directly supports a replicated, distributed file system. Hadoop on Nutanix can run without HDFS and interact with native storage, further increasing performance.
Nutanix Fits Your Big Data Strategy
If big data fits your business plans, dcVAST's managed Nutanix services can help you fit big data into your data center. We'll help you develop a strategy for managing your big data, then implement and support your Nutanix solution so that you can collect big data, share data cross processes, run analytics to find hidden insights, and report those insights to decision makers. With big data on Nutanix and help from dcVAST, the onrush of big data can support your processes rather than overwhelming them. Contact us to learn more about making big data and Nutanix part of your business and IT strategy.