Why use Hadoop for big data?

Have you ever wanted to store large types of data in one place without fear of data loss? It's time for you to take a look at Hadoop. 

It’s a tool that has gigantic storage power and great processing power to do repetitive tasks. 

Yes, we know that nowadays it’s necessary to have a large database to manage your business information. Well, now you will not have any excuse because Hadoop is the ideal ally. 

Would you like to see it with us?

What is Hadoop?

Let's start by defining what Hadoop is. It’s an open source framework that helps you store information and run different types of programs on basic hardware clusters. 

It has the ability to perform different types of activities and can store any type of data regardless of its characteristics. 

In this sense, we love the fact that it generates extremely fast responses to any kind of query about the data we store, all thanks to the distributed execution of code from several nodes in which each one processes part of the work. 

6 Reasons to use Hadoop

There are many reasons why you should take Hadoop as a real option from now on. Let's look at a few reasons below: 

1. It stores large amounts of data of any type.

First, it has the ability to store and process large amounts of data no matter what type it is. This is a key point, since at the end of the day the volumes and variety of data are constantly growing, so in one way or another it will become our ally. 

2. Tolerates failures

It’s likely that at some point were working and suddenly the computer shut down for no apparent reason. Well, with Hadoop you will be 100% protected against hardware failures because if a node has a problem, the jobs are passed to another to counteract the inconvenience.

In addition, multiple copies of the data are saved so that you can retrieve them whenever you want. 

3. Great processing power

We love the fact that the computing model used by Hadoop seamlessly processes big data, being able to run thousands of data in just a few seconds. 

So, the more nodes you have, the more processing power you get for your operations. 

4. Flexibility

A great advantage is that it’s 100% flexible, so you will not have to preprocess the data before saving it. You can store as much information as you need and then decide how you will use it. 

No matter what type of data is involved, unstructured, images or video.

5. Low cost

On the other hand, we can't forget that this framework being open source is free, so you won't have to pay anything out of your pocket, something that is more important than many people might think. 

In addition, it uses very basic hardware, so it’s very likely that the equipment you have is enough to start moving forward. 

6. Scalability

If you want to increase your processing capacity all you have to do is add more nodes to the network. At the end of the day, the more nodes you have the more data you can handle. 

Challenges of using Hadoop

Yes, unfortunately not everything is rosy, and while it has many plus points, it also has interesting challenges that you have to know about before you start using it. 

Would you like to see them?

1. Programming in MapReduce is not good for everything

One of the features of Hadoop is that it’s programmed with Mapreduce, something that doesn't fit all problems. The reality is that it’s very useful for simple requests and a few other drawbacks that can be split into separate units.

Nevertheless, it's very inefficient for analytical and interactive tasks, so someway or another you will have to use another alternative to be able to work properly. 

2. Well-recognized talent gap

One of the biggest problems we have encountered today is that it’s quite difficult to find programmers at a level that fits the needs of mapreduce and Java. 

That's why many technology vendors prefer SQL technology over Hadoop and it makes perfect sense. 

3. Data governance and management

It should be noted that the platform does not have comprehensive or easy-to-use tools to manage your data, do governance or clean up information that is no longer of use. 

This significantly complicates its daily use, so you should take this into account before making a decision. 

How to use Hadoop?

Let's now see the ways in which Hadoop is currently used. Pay close attention: 

1. Low-cost data archiving.

First of all we have the ability to archive data at very low cost. The cost of the equipment we use is useful for storing transactional, sensor, social network, scientific and other data. 

This way you can keep information that you may need in the future and that’s not considered of vital importance today. 

2. Data lake

Remember that data lakes give you the possibility of saving data in its original format, well structured or unstructured and without any processing which gives you a complete view without modifying the data to the analysts. 

In this way they will have new possibilities to ask different questions. 

3. Sandbox for analysis and discovery

It’s necessary to take into account that Hadoop was created to treat volumes of data in multiple ways without altering its originality. 

Now, with analytics in Hadoop, it allows the organization to work more efficiently, gain competitive advantages and discover new business opportunities. All this for a truly minimal investment. 

There’s no doubt that information is the treasure of companies in the 21st century. Backing it up and protecting it is one of your most important tasks as an entrepreneur if you want to take your business to the next level. 

Now is the time for you to use Hadoop to store any kind of data without having to worry about hardware failure. Back up your most relevant information and focus on the user experience. 

Are you ready to take the next step?