MATLAB vs Hadoop

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Our analysts compared MATLAB vs Hadoop based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

Hadoop Software Tool

Product Basics

MATLAB is a numerical computing and programming platform that enables users to develop and implement mathematical algorithms, create models and analyze data. Designed for engineers and scientists, it can be used for a range of purposes, including deep learning and machine learning, computational finance, image processing, predictive maintenance, IoT analytics and more. Built around its matrix-based programming language, it can help users run analyses on large data sets as well as design and rigorously test models.

It is available through on-premise installation on Windows and Mac. For eligible licensees, there is also a SaaS version accessible through a web browser. Users can purchase it under a perpetual or annual license, with discounts for academic institutions. For individuals not associated with government agencies, private companies or other organizations, there is a less expensive home license for personal use. Students can purchase a student license for a version designed for coursework and academic research.

Early-stage technology startups can apply for startup-friendly pricing and opportunities.
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Apache Hadoop is an open source framework for dealing with large quantities of data. It’s considered a landmark group of products in the business intelligence and data analytics space, and is comprised of several different components. It functions on basic analytics principles like distributed computing, large data processing, machine learning and more.

Hadoop is part of a growing family of free, open source software (FOSS) projects from the Apache Foundation, and works well in conjunction with other third-party products.
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Product Insights

  • Get Results Faster: Obtain quicker results through contextual hints, automatic code generation and a fully integrated debugger. Spend less time on programming and troubleshooting.
  • Analyze with Less Code: Teach the platform to automatically generate code to reproduce work and save time, as well as perform tasks such as training machine learning models or labeling data. 
  • Add-Ons For Every Application: Customize and extend the functionality of the core platform through the MATLAB family of add-on products to address specific business needs.
  • Scale Up to Big Data: Scale analyses to process big data by running on clusters, GPUs and clouds. Speed up computation on large data sets without needing to rewrite code or learn big data programming. 
  • Updates and Upgrades: Runs code more than twice as fast as before, due to continual updates and new features on the platform, as well as twice-yearly new releases.
  • Access Anywhere: Sign in to the online platform from any standard web browser, without needing to download and install the application on new machines. Syncs files between computers and the online platform via cloud storage and integration, eliminating the need for manual upload or download. 
  • Enhanced Collaboration: Collaborate by sharing scripts and files directly online or publishing to the web via interactive controls. Easily package or translate analysis for other platforms, or document work and export it to reports for sharing.
  • Free Trial: Try it hands-on with a free 30-day trial. Students whose schools have a campus license can access a free copy of the software without the 30-day trial limitation.
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  • Scalability: Hadoop's distributed computing model allows it to scale up from a single server to thousands of machines, each offering local computation and storage. This means businesses can handle more data simply by adding more nodes to the network, making it highly adaptable to the exponential growth of data.
  • Cost-Effectiveness: Unlike traditional relational database management systems that can be prohibitively expensive to scale, Hadoop enables businesses to store and manage vast amounts of data at a fraction of the cost, thanks to its ability to run on commodity hardware.
  • Flexibility: Hadoop is designed to efficiently process large volumes of data of different types, from structured to unstructured. This flexibility allows organizations to harness the power of big data without the constraints of a predefined schema, making it easier to make data-driven decisions.
  • Fault Tolerance: Hadoop automatically replicates data to multiple nodes, ensuring that the system is highly resilient to hardware failure. If a node goes down, tasks are automatically redirected to other nodes to ensure continuous operation, minimizing downtime and data loss.
  • Processing Speed: With its unique storage method based on a distributed file system that maps data wherever it is located on a cluster, Hadoop can process large volumes of data much more quickly than traditional systems. This speed makes it ideal for applications that require processing terabytes or petabytes of data, such as analyzing customer behavior patterns.
  • Efficient Data Processing: Hadoop's MapReduce programming model is designed for processing large data sets in parallel across a distributed cluster, which significantly speeds up the data processing tasks. This efficiency is crucial for performing complex calculations and analytics on big data in a timely manner.
  • Community Support: Being an open-source framework, Hadoop benefits from a vast community of developers and users who continuously contribute to its development and improvement. This community support ensures that Hadoop stays at the forefront of big data processing technology, with regular updates and a wide range of compatible tools and extensions.
  • Data Locality Optimization: Hadoop moves computation closer to data rather than moving large data sets across the network to be processed. This approach reduces the time taken to process data, as it minimizes network congestion and increases the overall throughput of the system.
  • Improved Business Continuity: The fault tolerance and high availability features of Hadoop ensure that businesses can maintain continuous operations, even in the face of hardware failures or other issues. This reliability is critical for organizations that depend on real-time data analysis for operational decision-making.
  • Enhanced Data Security: Hadoop includes robust security features, such as Kerberos authentication, to ensure that data is protected against unauthorized access. This security framework is essential for businesses that handle sensitive information, providing peace of mind that their data is secure.
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  • Data Import: Import and access a variety of data types, including text files, spreadsheets, images, audio, video, scientific data formats, IoT data, large data sets and more. 
  • Algorithm Development: Develop algorithms with thousands of core mathematical, engineering and scientific functions and tools for debugging, implementation and optimization. 
  • Automate with Machine Learning: Leverage interactive apps to see how algorithms work with data and then tweak to get the desired results. Then, automatically generate a program to reproduce or automate workflows. 
  • Live Editor: Build functions and generate code, creating scripts that can be enhanced with formatting through an interactive editor. Compile these scripts and results into an executable notebook. Explore parameters and immediately see the results, saving time.
  • Data Analysis: Analyze large data sets and big data in a multitude of ways through thousands of prebuilt functions for statistical analysis, machine learning and signal processing.
  • Data Visualization: Turn data into graphics with prebuilt 2D and 3D plots, including line plots, histograms, bar graphs, scatter plots, pie charts, word clouds, maps, polar plots, vector fields and animations.
  • Mathematics: Perform mathematical calculations via a vast library of mathematical functions, including linear algebra, statistics, Fourier analysis, numerical integration, differential equations and more.
  • Modeling: Supports model-based design, multi-domain simulation and automatic code generation via integration with another product from the same vendor, Simulink. Helps in numeric and symbolic modeling and provides mathematical tools like curve fitting, statistics, ODE and PDE solving, calculus and more.
  • Teach with Live Scripts: Build live scripts with its code to let students explore concepts and learn on their own. Create engaging lectures that walk students through explanations, math equations and results, one section at a time. Modify code on the fly to demonstrate how to use math to solve complex problems.
  • App Designer: Create, package and share professional desktop and web apps without needing all the technical know-how of app development. Lay out a graphical user interface through drag-and-drop tools and write the coding for the app’s behavior with an integrated editor and code analyzer that warns about errors in code as it’s written.
  • Community Gallery: See examples from the community on how to display and manipulate data by visiting the plot gallery and live script gallery on the vendor’s website.
  • Programming Integrations: Supports interfacing with other programming languages. Use the platform from within another programming environment without starting a new desktop session through engine APIs that support C/C++, Fortran, Java, Python and more. Call functions and objects from other libraries, including C, C++, Java, Python, .NET, COM objects and more from within the platform. Convert algorithms written in its code to C/C++.
  • Add-Ons: Utilize toolboxes and specialized solutions for fields such as math and optimizations, statistics and data science, code generation, application deployment, database access and reporting. These toolboxes are professionally built, rigorously tested and fully documented. Integrate automated reporting into the platform with richly-formatted custom reports in PDF, Word and HTML formats. 
  • MATLAB Online: Access the platform from any web browser through cloud-based services without downloading and installing the software. 
  • MATLAB Drive: Store, manage and share files from the cloud across devices and work with files from anywhere.
  • Mobile App: Learn and teach through mobile apps for iOS and Android devices. Connect to sessions, and acquire sensor data to analyze and capture images and videos.
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  • Distributed Computing: Also known as the Hadoop Distributed File System (HDFS), this feature can easily spread computing tasks across multiple nodes, providing faster processing and data redundancy in the event that there’s a critical failure. Hadoop is the industry standard for big data analytics. 
  • Fault Tolerance: Data is replicated across nodes, so even in the event of one node failing, the data is left intact and retrievable. 
  • Scalability: The app is able to run on less robust hardware or scale up to industrial data processing servers with ease. 
  • Integration With Existing Systems: Because Hadoop is so central to so many big data analytics applications, it integrates easily into a number of commercial platforms like Google Analytics and Oracle Big Data SQL or with other Apache software like YARN and MapR. 
  • In-Memory Processing: Hadoop, in conjunction with Apache Spark, is able to quickly parse and process large quantities of data by storing it in-memory. 
  • Hadoop MapR: MapR is a component of Hadoop that combines a number of features like redundancy, POSIX compliance and more into a single, enterprise grade component that looks like a standard file server. 
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Product Ranking

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User Sentiment Summary

Excellent User Sentiment 4535 reviews
Great User Sentiment 474 reviews
92%
of users recommend this product

MATLAB has a 'excellent' User Satisfaction Rating of 92% when considering 4535 user reviews from 5 recognized software review sites.

85%
of users recommend this product

Hadoop has a 'great' User Satisfaction Rating of 85% when considering 474 user reviews from 3 recognized software review sites.

4.5 (599)
4.3 (101)
4.6 (1808)
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4.6 (1570)
4.3 (244)
4.6 (401)
n/a
4.3 (157)
4.2 (129)

Awards

MATLAB stands above the rest by achieving an ‘Excellent’ rating as a User Favorite.

User Favorite Award

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Synopsis of User Ratings and Reviews

Service and Support: All users who mentioned support said that online community forums are supportive in helping them leverage the platform to its maximum potential.
Data Processing: Around 92% of users who discussed its data processing capabilities said that the solution helps to simulate and visualize complex mathematical models in an intuitive manner.
Data Analysis: According to 92% of users who reviewed data analysis, the platform, with multiple built-in packages, is useful in exploring data, creating machine learning models and predictive analysis.
Functionality: Citing a range of pre-loaded functions and algorithms, approximately 88% of users who reviewed functionality said that the solution is a powerful tool with a rich feature set and strong computing abilities.
Ease of Use: Reviewing ease of using the tool, approximately 60% of users said that, with detailed documentation being readily available, minimal coding experience is necessary to create and combine scripts.
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Scalability: Hadoop can store and process massive datasets across clusters of commodity hardware, allowing businesses to scale their data infrastructure as needed without significant upfront investments.
Cost-Effectiveness: By leveraging open-source software and affordable hardware, Hadoop provides a cost-effective solution for managing large datasets compared to traditional enterprise data warehouse systems.
Flexibility: Hadoop's ability to handle various data formats, including structured, semi-structured, and unstructured data, makes it suitable for diverse data analytics tasks.
Resilience: Hadoop's distributed architecture ensures fault tolerance. Data is replicated across multiple nodes, preventing data loss in case of hardware failures.
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Performance and Speed: Around 91% of users who reviewed speed said that the platform is resource-hungry in terms of power and space and slows down when performing complex computations.
Cost: Citing licensing costs, approximately 81% of users said that the software is expensive for individual users.
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Complexity: Hadoop can be challenging to set up and manage, especially for organizations without a dedicated team of experts. Its ecosystem involves numerous components, each requiring configuration and integration.
Security Concerns: Hadoop's native security features are limited, often necessitating additional tools and protocols to ensure data protection and compliance with regulations.
Performance Bottlenecks: While Hadoop excels at handling large datasets, it may not be the best choice for real-time or low-latency applications due to its batch-oriented architecture.
Cost Considerations: Implementing and maintaining a Hadoop infrastructure can be expensive, particularly for smaller organizations or those with limited IT budgets.
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MATLAB is a computing and programming tool that combines the power of functions and algorithms with data integration, modeling and visualization for predictive business data analysis. Users perform complex computations on data sets that the platform ingests from a multitude of data sources to glean business-specific metrics. Citing online communities, all users who reviewed support said that the tool is accessible to beginners, while providing enough depth for advanced users, though some said that the coding syntax could be daunting for non-technical users initially. Around 92% of users who reviewed its analytical capabilities said that the platform provides a wide range of built-in packages to provide out-of-the-box data analysis solutions. With its minimal scripting, many users who discussed data processing said that they could simulate complex mathematical functions to visualize complex data models. Reviewing its functionality, many users said that its rich library and design makes it possible to write powerful programs easily. A majority of users who discussed its performance said that the platform consumes a lot of power and space and slows down when performing complex computations, possibly because updates, though frequent, do not include optimization for older features. Many users who reviewed the cost said that individual user licenses are expensive, and buying additional libraries adds to the cost since many of these have interlinking dependencies, though some users said that the platform provides value for money. In summary, MATLAB is a programming solution that leverages machine learning for data collection and complex computations for users to create data models and visualize enterprise metrics for predictive analysis.

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Hadoop has been making waves in the Big Data Analytics scene, and for good reason. Users rave about its ability to scale like a champ, handling massive datasets that would make other platforms sweat. Its flexibility is another major plus, allowing it to adapt to different data formats and processing needs without breaking a sweat. And let's not forget about reliability – Hadoop is built to keep on chugging even when things get rough. However, it's not all sunshine and rainbows. Some users find Hadoop's complexity a bit daunting, especially if they're new to the Big Data game. The learning curve can be steep, so be prepared to invest some time and effort to get the most out of it. So, who's the ideal candidate for Hadoop? Companies dealing with mountains of data, that's who. If you're in industries like finance, healthcare, or retail, where data is king, Hadoop can be your secret weapon. It's perfect for tasks like analyzing customer behavior, detecting fraud, or predicting market trends. Just remember, Hadoop is a powerful tool, but it's not a magic wand. You'll need a skilled team to set it up and manage it effectively. But if you're willing to put in the work, Hadoop can help you unlock the true potential of your data.

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