...
Full Bio
Follow on
Security Tips to handle Digital Currency-Bitcoin
today
Famous Business Intelligence Tools for great Business Insights
today
What if two technologies Artificial Intelligence and Big Data are combined for new breakthroughs?
today
Free Tutorials on Machine Learning for a comprehensive learning
today
Every Programmer should strive for reading these 5 books
529902 views
Why you should not become a Programmer or not learn Programming Language?
183420 views
See the Salaries if you are willing to get a Job in Programming Languages without a degree?
138813 views
Highest Paid Programming Languages With Highest Market Demand
122646 views
Python Programming Language can easily be acquired easily. How?
108972 views
See some Best-Known Big Data tools, their Advantages and Disadvantages to Analyze your Data
Enlisted below are some of the top open source tools and few paid commercial tools that have a free trial available.
So here are some Big Data Analytics tools which we will explore in detail in this article.
1) Apache Hadoop
Apache Hadoop is a software framework employed for clustered file system and handling of big data. It processes datasets of big data by means of the MapReduce Programming model.
Hadoop is an open source framework that is written in Java and it provides cross-platform support.
No doubt, this is the topmost big data tool. In fact, over half of the Fortune 50 companies use Hadoop. Some of the Big names include Amazon Web services, Hortonworks, IBM, Intel, Microsoft, Facebook, etc.
Advantages:
- The core strength of Hadoop is its HDFS (Hadoop Distributed File System) which has the ability to hold all type of data - video, images, JSON, XML, and plain text over the same file system.
- Highly useful for R&D purposes.
- Provides quick access to data.
- Highly scalable
- Highly-available service resting on a cluster of computers
Disadvantages:
- Sometimes disk space issues can be faced due to its 3x data redundancy.
- I/O operations could have been optimized for better performance.
Click here to visit the Apache Hadoop Website.
2) CDH (Cloudera Distribution for Hadoop)
CDH aims at enterprise-class deployments of that technology. It is totally open source and has a free platform distribution that encompasses Apache Hadoop, Apache Spark, Apache Impala, and many more.
It allows you to collect, process, administer, manage, discover, model, and distribute unlimited data.
Advantages:
- Comprehensive distribution
- Cloudera Manager administers the Hadoop cluster very well.
- Easy implementation.
- Less complex administration.
- High security and governance
Disadvantages:
- Few complicating UI features like charts on the CM service.
- Multiple recommended approaches for installation sounds confusing.
- However, the Licensing price on a per-node basis is pretty expensive.
Click here to visit the CDH (Cloudera Distribution for Hadoop) Website.
3) Cassandra
Apache Cassandra is free of cost and open-source distributed NoSQL DBMS constructed to manage huge volumes of data spread across numerous commodity servers, delivering high availability. It employs CQL (Cassandra Structure Language) to interact with the database.
Some of the high-profile companies using Cassandra include Accenture, American Express, Facebook, General Electric, Honeywell, Yahoo, etc.
Advantages:
- No single point of failure.
- Handles massive data very quickly.
- Log-structured storage
- Automated replication
- Linear scalability
- Simple Ring architecture
Disadvantages:
- Requires some extra efforts in troubleshooting and maintenance.
- Clustering could have been improved.
- The row-level locking feature is not there.
Click here to visit the Cassandra Website.
4) Knime
KNIME stands for Konstanz Information Miner which is an open source tool that is used for Enterprise reporting, integration, research, CRM, data mining, data analytics, text mining, and business intelligence. It supports Linux, OS X, and Windows operating systems.
It can be considered as a good alternative to SAS. Some of the top companies using Knime include Comcast, Johnson & Johnson, Canadian Tire, etc.
Advantages:
- Simple ETL operations
- Integrates very well with other technologies and languages.
- Rich algorithm set.
- Highly usable and organized workflows.
- Automates a lot of manual work.
- No stability issues.
- Easy to set up.
Disadvantages:
- Data handling capacity can be improved.
- Occupies almost the entire RAM.
- Could have allowed integration with graph databases.
Click here to visit the Knime Website.
5) Datawrapper
Datawrapper is an open source platform for data visualization that aids its users to generate simple, precise and embeddable charts very quickly.
Its major customers are newsrooms that are spread all over the world. Some of the names include The Times, Fortune, Mother Jones, Bloomberg, Twitter, etc.
Advantages:
- Device friendly. Works very well on all type of devices' mobile, tablet or desktop.
- Fully responsive
- Fast
- Interactive
- Brings all the charts in one place.
- Great customization and export options.
- Requires zero codings.
Disadvantages: Limited color palettes
Click here to visit the Datawrapper Website.
6) MongoDB
MongoDB is a NoSQL, document-oriented database written in C, C++, and JavaScript. It is free to use and is an open source tool that supports multiple operating systems including Windows Vista ( and later versions), OS X (10.7 and later versions), Linux, Solaris, and FreeBSD.
Its main features include Aggregation, Adhoc-queries, Uses BSON format, Sharding, Indexing, Replication, Server-side execution of javascript, Schemaless, Capped collection, MongoDB management service (MMS), load balancing and file storage.
Some of the major customers using MongoDB include Facebook, eBay, MetLife, Google, etc.
Advantages:
- Easy to learn.
- Provides support for multiple technologies and platforms.
- No hiccups in installation and maintenance.
- Reliable and low cost.
Disadvantages:
- Limited analytics.
- Slow for certain use cases.
Click here to visit the MongoDB Website.
7) Lumify
Lumify is a free and open source tool for big data fusion/integration, analytics, and visualization.
Its primary features include full-text search, 2D and 3D graph visualizations, automatic layouts, link analysis between graph entities, integration with mapping systems, geospatial analysis, multimedia analysis, real-time collaboration through a set of projects or workspaces.
Advantages:
- Scalable
- Secure
- Supported by a dedicated full-time development team.
- Supports the cloud-based environment. Works well with Amazonâ??s AWS.
Click here to visit the Lumify Website.
8) HPCC
HPCC stands for High-Performance Computing Cluster. This is a complete big data solution over a highly scalable supercomputing platform. HPCC is also referred to as DAS (Data Analytics Supercomputer). This tool was developed by LexisNexis Risk Solutions.
This tool is written in C++ and a data-centric programming language knowns as ECL(Enterprise Control Language). It is based on a Thor architecture that supports data parallelism, pipeline parallelism, and system parallelism. It is an open source tool and is a good substitute for Hadoop and some other Big data platforms.
Advantages:
- The architecture is based on commodity computing clusters which provide high performance.
- Parallel data processing.
- Fast, powerful and highly scalable.
- Supports high-performance online query applications.
- Cost-effective and comprehensive.
Click here to visit the HPCC Website.
9) Storm
Apache Storm is a cross-platform, distributed stream processing, and fault-tolerant real-time computational framework. It is free and open-source. The developers of the storm include Backtype and Twitter. It is written in Clojure and Java.
Its architecture is based on customized spouts and bolts to describe sources of information and manipulations in order to permit batch, distributed processing of unbounded streams of data.
Among many, Groupon, Yahoo, Alibaba, and The Weather Channel are some of the famous organizations that use Apache Storm.
Advantages:
- Reliable at scale.
- Very fast and fault tolerant.
- Guarantees the processing of data.
- It has multiple use cases real-time analytics, log processing, ETL (Extract-Transform-Load), continuous computation, distributed RPC, machine learning.
Disadvantages:
- Difficult to learn and use.
- Difficulties with debugging.
- Use of Native Scheduler and Nimbus become bottlenecks.
Click here to visit the Storm Website.
10) Apache SAMOA
SAMOA stands for Scalable Advanced Massive Online Analysis. It is an open source platform for big data stream mining and machine learning.
It allows you to create distributed streaming machine learning (ML) algorithms and run them on multiple DSPE's (distributed stream processing engines). Apache SAMOA's closest alternative is BigML tool.
Advantages:
- Simple and fun to use.
- Fast and scalable.
- True real-time streaming.
- Write Once Run Anywhere (WORA) architecture.
Click here to visit the Apache SAMOA Website.
11) Talend
Talend Big data integration products include:
Open studio for Big data: It comes under free and open source license. Its components and connectors are Hadoop and NoSQL. It provides community support only.
Big data platform: It comes with a user-based subscription license. Its components and connectors are MapReduce and Spark. It provides Web, email, and phone support.
Real-time big data platform: It comes under user based subscription license. Its components and connectors include Spark streaming, Machine learning, and IoT. It provides Web, email, and phone support.
Advantages:
- Streamlines ETL and ELT for Big data.
- Accomplish the speed and scale of spark.
- Accelerates your move to real-time.
- Handles multiple data sources.
- Provides numerous connectors under one roof, which in turn will allow you to customize the solution as per your need.
Disadvantages:
- Community support could have been better.
- Could have an improved and easy to use interface
- Difficult to add a custom component to the palette.
Click here to visit the Talend Website.
12) Rapidminer
Rapidminer is a cross-platform tool which offers an integrated environment for data science, machine learning and predictive analytics. It comes under various licenses that offer small, medium and large proprietary editions as well as a free edition that allows for 1 logical processor and up to 10,000 data rows.
Organizations like Hitachi, BMW, Samsung, Airbus, etc have been using RapidMiner.
Advantages:
- Open source Java core.
- The convenience of front-line data science tools and algorithms.
- The facility of code-optional GUI.
- Integrates well with APIs and cloud.
- Superb customer service and technical support.
Disadvantages:
Online data services should be improved.
Click here to visit the Rapidminer Website.
13) Qubole
Qubole data service is an independent and all-inclusive Big data platform that manages, learns and optimizes on its own from your usage. This lets the data team concentrate on business outcomes instead of managing the platform.
Out of the many, few famous names that use Qubole include Warner music group, Adobe, and Gannett. The closest competitor to Qubole is Revulytics.
Advantages:
- Faster time to value.
- Increased flexibility and scale.
- Optimized spending
- Enhanced adoption of Big data analytics.
- Easy to use.
- Eliminates vendor and technology lock-in.
- Available across all regions of the AWS worldwide.
Click here to visit the Qubole Website.
14) Tableau
Tableau is a software solution for business intelligence and analytics which present a variety of integrated products that aid the world's largest organizations in visualizing and understanding their data.
The software contains three main products i.e.Tableau Desktop (for the analyst), Tableau Server (for the enterprise) and Tableau Online (to the cloud). Also, Tableau Reader and Tableau Public are the two more products that have been recently added.
Tableau is capable of handling all data sizes and is easy to get to for technical and non-technical customer base and it gives you real-time customized dashboards. It is a great tool for data visualization and exploration.
Out of the many, few famous names that use Tableau includes Verizon Communications, ZS Associates, and Grant Thornton. The closest alternative tool of Tableau is the looker.
Advantages:
- Great flexibility to create the type of visualizations you want (as compared with its competitor products).
- Data blending capabilities of this tool are just awesome.
- Offers a bouquet of smart features and is razor sharp in terms of its speed.
- Out of the box support for connection with most of the databases.
- No-code data queries.
- Mobile-ready, interactive and shareable dashboards.
Disadvantages:
- Formatting controls could be improved.
- Could have a built-in tool for deployment and migration amongst the various tableau servers and environments.
Click here to visit the Tableau Website.
15) R
R is one of the most comprehensive statistical analysis packages. It is open source, free, multi-paradigm and dynamic software environment. It is written in C, Fortran and R programming languages.
It is broadly used by statisticians and data miners. Its use cases include data analysis, data manipulation, calculation, and graphical display.
Advantages:
- R's biggest advantage is the vastness of the package ecosystem.
- Unmatched Graphics and charting benefits.
Disadvantages: Its shortcomings include memory management, speed, and security.
Source: HOB