Is Hadoop Hot Or Cold?

If your business handles and processes huge amounts of data, Hadoop is likely a large part of your business operations.

With that said, open source data processing is growing in popularity and other forms of data management are becoming readily available.

Here are a few key benefits of Hadoop as well as other open source data processing platforms:

Hadoop and Business

Open source data processing gives businesses of all shapes and sizes flexibility, which is a major benefit in an ever-changing business world.

With Hadoop, your business has the ability to quickly store data as opposed to traditional forms of data storage where processing must take place first.

In addition, Hadoop also makes it possible to store unstructured data including images, videos, and text-based data.

This means your business is able to immediately store almost any type of data and decide how to use that data later down the road.

When it comes to data amounts, Hadoop again delivers. Hadoop is able to handle massive data sets. This is hugely beneficial in today's business world where social media data and incoming data from smart devices is on the rise.

Cost and Scalability

As mentioned above, the business landscape is ever-changing, especially when it comes to data management.

With that said, your budgeting goals probably need to stay the same. Fortunately, because Hadoop is anchored in an open-source framework and commodity software, it's extremely cost-effective.

The expandable nature of Hadoop also lends itself to scalability. Startups and small businesses can use small amounts of data processing based on their budgetary constraints.

Likewise, larger corporations can quickly increase their processing to meet their needs and their growing budgets.

Open Source Options on the Rise

Whether your business uses Hadoop or not, it's always wise to keep your options open when it comes to data processing.

The article "Spark: Catching Fire With or Without Hadoop" mentions some of the benefits of using open source data processing platforms such as Apache Spark.

Spark isn't a total replacement for Hadoop, but rather a tool that can actually help boost Hadoop's performance.

With the increased processing power of Spark, your business can improve performance across any number of workloads as well as workload subsets.

Benefits of Spark

Streamlined, efficient data processing is the goal for businesses of all kinds.

Data processing just so happens to be where Apache Spark really shines. When used in combination with Hadoop, Spark provides much faster batch processing.

Spark also offers interactive processing, which allows for changes to be made in the moment as opposed to after data reaches the storage stage. Spark even makes way for event stream processing.

The Hadoop and Spark partnership allows your business to run any number of tools in the Hadoop infrastructure.

Data Processing for Your Business

When it comes to adopting open source data processing at your business, the choice is up to you.

Hadoop may be enough processing power for your needs. However, Spark could give you the boost in processing speed that you're looking for.

Weigh your options, take a close look at your data, and decide whether Hadoop and Spark are necessary - there's a good chance they are.

If you're trying decide whether open source processing is a necessity for your business, consider some of the points mentioned above.