10 years ago

The Storage System for Big Data

Share in:
LinkedIn
Facebook
Twitter/X
Email
Share in:

Object-based storage typically handles billions and billions of files and can be scaled to accommodate very high volumes of data.

Ah big data. Chances are, your organization is trying its best to harness big data for your own purposes. Whether it is to learn more about your operations, your customers or process, or to try to find out more about what products are more likely to succeed, or to get insights, big data is simply a must for every organization to remain competitive today.

And while a lot of people are scrambling to find solutions and platforms that allow them to gather and analyze big data, they would also need to store all that data somewhere.

What should you be looking for in big data storage?

At the very core of your storage decisions as far as big data is concerned is that you should be looking for solutions that:

  1. Can handle and store huge amounts of data.
  2. Can scale as the need arises, meaning that you can grow your storage as your data also grows.
  3. Has a high input and output operations per second that would be needed if you are going to analyze all that data.

In short, it should be able to handle the big volumes of data and allow you to work with it quickly.

No idea where to start?

Google, Facebook, Apple and other companies that are currently handling tremendous amounts of data make use of hyperscale computing environments. Hyperscale computing environments make use of commodity servers that have direct attached storage or DAS. Everything is redundant so that if one unit fails, you can failover to your backup or mirror. Hyperscale computing environments often run on NoSQL, Cassandra or Hadoop and makes use of PCIe flash storage in addition to the disks to make sure that access to the data remains fast and involves less latency.

You can also use clustered or scale-out NAS. This type of storage can be scaled as you need more space and makes use of parallel file systems. Data is distributed across many nodes and, as such, a NAS storage can handle and transmit millions of files without slowing down your entire system, even as your data grown.

Another storage system for big data is object-based storage. Similar to cluster NAS, object-based storage also lets you store large amounts of data, scale out as needed and make way for fast processing of data. With an object-based storage, your files are given a unique identifier. The system then indexes these identifiers together with the data and the location. It works like a domain name system for the Internet, only that you are working with data in your own system.

Object-based storage typically handles billions and billions of files and can be scaled to accommodate very high volumes of data.

Which type of storage do you need for your business? And how do you go about purchasing and deploying the storage that you have chosen for your big data operations? Call Four Cornerstone today at 1 (817) 377 1144 and find out what you need to do to store all the data you can capture and will need. Our team of IT experts will be able to help you decide on an appropriate solution while providing low latency for your analytics.

Photo by Juhan Sonin.

Scroll to Top