depending on your project needs, Hadoop MapReduce and Apache Spark are two of the most popular tools in the industry

Apache spark has many libraries for data science, MLlib provide mchine learning

R is a good choice. Free license, a large community of users and lots of packages.

It depends on the concrete problem you want to address. For some tasks, MatLab can be taken into consideration as a bottom line solution.

depending on your project needs, Hadoop MapReduce and Apache Spark are two of the most popular tools in the industry

big data.” This name also makes a good sense because since the times of “business intelligence” the volumes of data became incredibly large. As the result, more effort should be applied to deal with them and make it useful for analytics professionals.

In this article, we have compiled a list of the top ten big data tools that are used by successful analytics developers.

1. Cassandra

This tool is widely used today because it provides an effective management of large amounts of data. It is a database that offers high availability and scalability without compromising the performance of commodity hardware and cloud infrastructure. Among the main advantages of Cassandra highlighted by the development are fault tolerance, performance, decentralization, professional support, durability, elasticity, and scalability. Indeed, such users of Cassandra as eBay and Netflix may prove them.

2. Hadoop

Another great product from Apache that has been used by many large corporations. Among the most important features of this advanced software library is superior processing of voluminous data sets in clusters of computers using effective programming models. Corporations choose Hadoop because of its great processing capabilities plus developer provides regular updates and improvements to the product.

3. Plotly

Successful big data analytics use Plotly to create great dynamic visualization even in case if the company does not have sufficient time or skills for meeting big data needs. It makes the process of creating stunning and informative graphics very easy using the online tools. Also, the platform enables sharing the findings by transporting the results into different convenient formats.

4. Bokeh

Similarly to Plotly, this tool is also great for creating easy and informative visualizations. It is used for big data analytics experts to easily and quickly create interactive data applications, dashboards, and plots. Check out the gallery of the example works that were done with Bokeh using the big data. Many experts also say Bokeh is the most advanced visual data representation tool.

5. Neo4j

The official website of the tool claims that it is the world’s leading graph database. Indeed, it is, because it takes the big data business to the next level: it helps to work with the connections between them. The connections between the data drive modern intelligent applications, and Neo4j is the tool that transforms these connections to gain competitive advantage. If you are looking for additional information about how you can gain a competitive advantage of utilizing a graph database, check out this white paper.

6. Cloudera

Businesses today use this tool for creating a data repository that can be accessed by all corporate users that need the data for different purposes. It was developed in 2008 and still is the most popular provider and supporter of Apache Hadoop. This combination is known to transform businesses and reducing business risks in order to give them a competitive advantage.

7. OpenRefine

Need to explore voluminous data sets with ease? This tool allows the businesses to prepare everything for the data analysis. Simply saying, OpenRefine will help to organize the data in the database that was nothing but a mess. As the result, the users can begin to process the data with the computer.

8. Storm

This tool makes the list because of its superior streaming data processing capabilities in real time. It also integrates with many other tools such as Apache Slider to manage and secure the data. The use cases of Storm include data monetization, real time customer management, cyber security analytics, operational dashboards, and threat detection. These functions provide awesome business opportunities.

9. Wolfram Alpha

Want to calculate or know something new about things? Wolfram Alpha is an awesome tool to look for information about just about everything. Doug Smith from Proessaywriting says that his company uses this platform for advanced research of financial, historical, social, and other professional areas. For example, if you type “Microsoft,” you receive input interpretation, fundamentals and financials, latest trade, price history, performance comparisons, data return analysis, correlation matrix, and many other information.

10. Rapidminer

A big data specialist needs this open source data science platform, which functions through visual programming. It allows to manipulate, analyze, model, create models, and integrate the data into business processes.

I will go with Apache Spark, as It has machine learning libraries, can use python and R libraries, can used scala and Java to code new ideas, multi-Source, has its own performance boosters like in-memory processing, scalable, and keeps evolving faster than any other tools.

Best Regards.