Commodity hardware refers to off-the-shelf hardware you can readily purchase from computer and accessory shops. They are typically affordable and can work with all kinds of devices so long as they’re compatible.

Commodity hardware includes servers, cables, and practically everything you need to use or connect computing or IT devices in a network. They are plug-and-play, meaning they should make your gadget work when connected. An example would be the cables you use to connect servers together. You don’t need to activate them to make them work. Just plug them into the correct ports, and you’re good to go.

Other interesting terms…

Read More about “Commodity Hardware

Commodity hardware came about to make networking more affordable for organizations. Instead of purchasing a redundant array of independent disks (RAID) server that can cost between US$5,000 and US$20,000, companies can turn an ordinary server worth around US$600 into a RAID server using commodity hardware.

Why Do Companies Need RAID Servers?

Given the current state of the threat landscape where attackers go after organizations, regardless of size, all businesses need to ensure their operations that heavily rely on computing are always up and running. Distributed denial-of-service (DDoS) attacks can easily cause their websites to go offline. But if they turn ordinary servers into RAID servers using commodity hardware, they won’t have to worry. RAID servers are usually fault-tolerant, meaning they have backups that spin up when your primary servers shut down.

If the company’s network gets infected with ransomware, it can continue operating using the backup data. Even if it fails to get its files back from the threat actors, it will still have the information it requires.

What Are the Benefits of Commodity Hardware?

This type of hardware, as mentioned earlier, makes it possible for even financially constrained organizations to ensure 100% uptime and enable fast disaster recovery. They are:

  • Inexpensive: Commodity hardware costs much less than purchasing its branded counterparts.
  • Easy to use: Because they’re compatible with most systems, they don’t require configuration and much fine-tuning.
  • Highly available: Commodity hardware is readily available in computer and IT shops.
  • Ensures quick disaster recovery: Using commodity hardware for off-site backups ensures that your operations will continue despite natural disasters or emergencies in your office site.
  • Continued access to data: The information your business needs can be kept safe in a different location, so you can enjoy business as usual even if you suffer from a cyber attack.

Does Using Commodity Hardware Require Hadoop?

To connect and use commodity hardware together, organizations need Hadoop—an open-source arrangement that allows users to achieve parallelism. Parallelism refers to utilizing techniques to make programs run faster or perform multiple computations simultaneously. Without Hadoop, turning a typical server into a RAID server may not be possible.

Using Hadoop ensures the following on commodity hardware:

  • Scalability: You can use as many servers as available, especially when processing big data.
  • Low cost: You may not need to purchase costly hardware to process vast amounts of data.
  • Flexibility: You can purchase only the required number of servers for your usual data load.
  • Fault tolerance: You always have a backup of all the data because each data point gets copied on two servers.
  • Computing power: You don’t need servers with high processing power. Even low-end servers will work so long as you have enough of them.
  • Ability to process and store vast amounts of any data: You can match your server number with the size of your data set.

How Does Hadoop Work in Commodity Hardware?

Commodity hardware users must install Hadoop on all servers. That distributes data for processing or analysis among them. As a result, each server will have some data, but none will have all the data. Some data points are copied on two servers to ensure they don’t get lost when issues arise. That is parallelism at work. All the servers process the entire dataset simultaneously to achieve one objective.

Commodity hardware has made networking and big data processing more affordable for even the smallest organization.