According to an article published in economic times, Big Data analytics is expected to be the most in-demand skill in 2022.

With the adoption of technology across all industries at an alarming rate, the industries are going to be entirely tech-enabled.

Where there is technology, there is Big Data. Big Data is considered gold today. Big data Analytics is a promising career because the volume of data generated every second by people around the world is still increasing.

Data is nothing until it is in a usable format. So it is strongly required that you process these huge chunks of data. ‘

Traditional data tools are not capable of handling massive volumes of data generated and that’s why there are custom-built tools to help you out. These Big Data tools help businesses to put their data to work, to establish the latest business models, as well as establish business models.

This is why there is a huge increase in the demand for professional experts in analytics and other big data tasks. Big Data courses have got a good hype among these professionals.

Let’s look at some of the most popular Big Data tools out there in the market.

Top X Big Data Tools

  1. Xplenty

One of the most popular Big Data tools, Xplenty enables you to integrate, process, and assemble data for analytics on the cloud. It puts together all the sources of data. It helps you in implementing ETL(Extract, Transform, Load), or other replication solutions with its intuitive graphic interface.

Xplenty is a scalable and elastic cloud platform. It provides you with immediate connectivity to various data sources and a huge set of data transformation components.

It also allows you to implement complex functions for data preparation by using the rich expression language of Xplenty. To provide advanced customization and flexibility, it offers API(Application Programming Interface) components.

  1. Hevo Data

This is a Big Data integration or ETL tool. It is a fully automated platform and requires no maintenance. It is capable of automating data flow in just a few moments. Hevo is a simple and interactive UI that offers real-time data migration.

Hevo is built to detect the schema of incoming data and automatically maps it to the destination schema. With the increasing volume of data and an increasing number of sources, Hevo is capable of handling millions of records per minute by scaling the data horizontally.

You can view all the activities that take place within the pipeline with the live monitoring feature of Hevo. The team of Hevo is available for you round-the-clock support via calls, emails, and chats.

  1. Apache Hadoop

Apache Hadoop is the most popular Big Data tool which is used widely across the world. Hadoop is an open-source and free tool meant for managing distributed processing of Big Data across a computer network.

With HTTP servers, Hadoop provides a high level of security to your data. Instead of storing all the data in a single system, it clusters several computers into a scalable network and analyses the data in parallel.

The most important feature of this tool is that it provides for simple and fast processing of data with distributed processing.

  1. Apache Spark

Another free and open-source tool by Apache, Spark is also concerned with distributed processing of data by connecting numerous computers by which the processing goes simple and quick.

The efficiency and speed of Spark make it preferable for machine learning and other related applications. Spark has a collection of tools that introduces a wide range of features that includes Spark streaming, graph data processing, advanced APIs in Python, Scala, and R.

The most important thing to note is that Spark applications are capable of running 100 times faster in memory and ten times faster on storage.

  1. Apache Storm

Apache Storm is an open-source Big Data Analytics tool that is capable of handling unbounded data streams. Its fault-tolerant and real-time processing system are compatible with all the programming languages.

The key feature of Apache Storm is that it can handle 1 million 100-byte messages per node per second. It uses a cluster of devices for performing parallel calculations. The tool is known for its simplicity.

  1. Apache Cassandra

It is a NO-SQL or non-relational database that is known for offering huge scale, continuous availability, and data dispersion across various Cloud Availability zones and data centers.

Did you know that the open-source version of Apache Cassandra is famous for having the largest deployment at Apple?

Netflix is another significant user of this popular Big Data tool.

High fault tolerance and reduced user delays are some of the key features of Cassandra.

  1. Zoho Analytics

It is the most easy-to-use and cost-effective tool meant for Big Data Analytics when it comes to small businesses. It has a very simple interface that enables you to build sophisticated dashboards and recognize the most critical data quickly.

While being efficient as a stand-alone tool, it has the unique feature of being directly integrated with the rest of the business tools in the Zoho suite including HR, CRM, and Marketing Automation.

Zoho Analytics has pre-built and easily usable analytical functions. Its dashboards make it easily accessible to non-IT users.

  1. Rapid Miner

An open-source Big Data Analytics tool, Rapid Miner is capable of handling model deployment, data preparation, as well as Machine Learning model development.

It’s known for its efficiency even when used in parallel with Cloud services and APIs. it offers various data management approaches and has a simple GUI (Graphical User Interface).

Rapid Miner has interactive and shared dashboards. It also allows for batch processing.

  1. Cloudera

Now comes one of the most secure and quickest Big Data Analytics tools out there in the market. This is a flexible platform that makes it simple to collect data from any setting. It allows you to perform real-time monitoring and insights. This tool can be deployed on Google Cloud, AWS, Microsoft Azure, and other cloud platforms. It also allows you to build and train data models. 

The best feature of Cloudera it allows you to pay only for what and when you need it.

  1. Apache Hive

It is another free and open-source Big Data solution that allows Hadoop programmers to process huge data collections. To conduct SQL-type queries, it uses HQL (Hive Query Language) and then transforms it to MapReduce tasks internally. It assembles the language with a map and reducer.

Also, it allows you to code in Java or Python. It also includes a Java Database Connectivity interface.


Now that you have got a brief introduction to some of the most popular Big Data Analytics tools, you can take up an online training course to master these tools. With actual use-cases and real-life projects, these courses allow you to gain expertise in these Big Data tools.

By mastering these tools you can land a great job in this domain. Also, Big Data professionals are offered huge salaries.

Enroll Yourself Now!!

By Manali