9 Most Popular Big Data Consulting Development Tools In 2020

Today, the market is full of big data consulting development tools. Almost all companies use these tools to be better and improve their business. The competition in the Big Data market is enormous. Big Data tools help in knowing marketing, generating offers benefits to both parties, and increasing loyalty and engagement. Thus, for coming up with the best tools, there are various pros and cons to look out for in each one of them. You should certainly look out for them to achieve excellent results in your business. So, for that, here are the nine most popular Big Data consulting development tools in 2020.

Apache Hadoop
Apache Hadoop is among the best Big Data development tools. It is also known for providing support in cross-platform app development. Hadoop is an open-source framework. It is written using Java. Hadoop is also the first choice for R&D purposes. Designed for scaling one server to many, a lot of fortune 50 companies like AWS, IBM, and Facebook prefer Hadoop. So, here are the key features of Hadoop:

HDFS or Hadoop Distributed File System can hold all kinds of data, be it an image, video, or even an XML file, on the same system. The better part is that there are many modules like this one on Hadoop. Few are Hadoop YARN, Hadoop Common, and Hadoop MapReduce.
 
•    Highly authenticated HTTP server
    
•    Scalable and provides quick access to all data

•    Fast and flexible data processing

Apache Spark
Spark is another open-source framework by Apache. Written in Java, it is an excellent option for Machine Learning and Data Analytics. Spark can process data way quicker than conventional disk processing. Just like its name, it is fast as a spark. It even helps in SQL processing and streaming. Thus, here are a few features of Apache Spark:
    
•    It can manage real-time data and yet batch data at the same time
    
•    Up to 100x quicker than MapReduce
    
•    Very easy to use

•    Super easy development and testing

Cloudera
Cloudera or CDH which is Cloudera Distribution for Hadoop is an open-source platform for collecting and allotting data. It is also regarded for providing Enterprise data cloud, even to AI. Cloudera is a top certification path acting as a platform for machine learning and analytics. Here are some features of Cloudera:
    
•    Scalable and easy to use
    
•    One of the most secure platforms
    
•    Easy administration and detailed distribution

•    Multi-cloud provision

Cassandra
Cassandra by Apache is an open-source platform and an amazing big data consulting tool. Java is the language used in Cassandra. It is a NoSQL system controlling large amounts of data across many servers. Additionally, it also offers third party offers. Moreover, Cassandra is the choice of big companies like Facebook, Accenture, and Yahoo. Thus, the following are its features:
    
•    Makes use of the Cassandra Structure Language
    
•    Robust, high scalability and availability
    
•    Auto replication and high fault tolerance
    
•    SPOF mechanism (no single point of failure)

•    Preferred for apps that should not lose data at any cost no matter what

Qubole
Qubole is an independent Big Data consulting tool. It can control as well as enhance performance from your usage. Qubole is a platform native to the cloud. It has an extensive client network, its main clients being Adobe and Warner Music Group. Following are its features:
    
•    Flexible and Scalable
    
•    Easy to use and adopt
    
•    Available all over the world (AWS regions)
    
•    Can reduce computing cost by almost a half

•    Makes use of user-end-tools

Xplenty
Xplenty is a big data analytics tool. It is also an ETL solution giving simple data for automatic flows of data around the world. Moreover, this tool is equipped with on-platform transformation tools for data. Big businesses use the device like Grofers and Bexio. The following are its key features:

•    Flexible and code-free
    
•    Possible to integrate data from different sources
    
•    Makes use of REST API

•    24/7 Support

MongoDB
MongoDB is an open-source tool also used for big data consulting. It is a NoSQL database supporting cross-platform development. MongoDB can also run on various platforms like Java and NET. It is written in C++ and JS. Tech giants like Facebook, Google, and eBay use this tool. Thus, here are some features:
    
•    Flexible and easy to spread data to many servers
    
•    Saves cost as it makes use of dynamic schemes
    
•    Easy to learn and reliable

•    Good customer support

Lumify
Lumify is a great open-source data consulting tool also used for data analytics and integration. Additionally, this tool has a wide range of analytic options for the user to discover and explore new connections. The device also supports real-time collaboration, multimedia, and geospatial analysis. So, let's take a look at Lumify’s key features:

•    Highly scalable and secure
        
•    Provides 24/7 customer support
    
•    2D and 3D visualizations

•    Has auto layouts and link analysis

Apache SAMOA
Apache SAMOA is an open-source big data consulting and mining tool. Other than mining, SAMOA is also used for clustering, regressing, and classifying data. It runs on DSPE (Distributed Stream Processing Engines) which helps in allowing the development of new algorithms. This tool can also help in machine learning tasks. Moreover, it has a lot of advantages and features, a few of them being:
    
•    Pluggable and reusable architecture (WORA)
    
•    No downtime or update processes
    
•    Only requires to be programmed once and then can be run everywhere
    
•    Fast and easy to use

•    Scalable, fun to learn, and highly trusted.

Summing Up
If you want to get into big data, these are the best tools you can compare and choose. Additionally, there are many other tools, open-source, and paid. But, if you are just starting, it is always better to go with an open-source tool. Choosing a big data tool needs to be done patiently. Thus, you must try out all the proper tools and then come up with a choice. Another good idea is to try out the demo versions of specific paid tools to get an idea of how they work and how it will benefit you.