Hadoop vs WebFOCUS

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Our analysts compared Hadoop vs WebFOCUS 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
WebFOCUS Software Tool

Product Basics

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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WebFOCUS is a comprehensive data management and analytics platform that enables organizations to access, transform, visualize, and distribute data across multiple platforms. It's particularly well-suited for enterprises with large, complex datasets and a need for robust reporting and analytics capabilities. Key benefits include its ability to unify disparate data sources, create interactive dashboards and visualizations, and automate data-driven workflows. Popular features include its drag-and-drop report builder, self-service data exploration tools, and integration with various business intelligence applications. User experiences generally praise its ease of use, scalability, and ability to handle diverse data types. Pricing is typically based on the number of users, data sources, and required features, with options for both on-premise and cloud-based deployments.

Pros
  • Easy to use interface
  • Handles large datasets
  • Diverse data source integration
  • Customizable reports and dashboards
  • Scalable for enterprise needs
Cons
  • Occasional performance issues
  • Limited out-of-the-box visualizations
  • Upgrades can be complex
  • UI may feel outdated to some
  • Learning curve for advanced features
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$50/Three Concurrent Users, Annually
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Product Assistance

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Knowledge Base
24/7 Live Support
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Product Insights

  • 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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  • Ease of Use: Everyone can access and derive rich insights and helpful information from enterprise data through an intuitive GUI with drag-and-drop ease. Increase adoption and encourage self-service data exploration at all levels of technical knowledge.
  • Make Better Decisions: Empower smarter, more consistent and more accurate proactive decision-making throughout the organization.
  • Faster Time to Insight: Streamline data workflows and analytics processes and efficiently access the most relevant insights through a personalized, interactive home page and enhanced content search.
  • Scalable: Deploy to millions and customize the solution to business needs. Scale up or down, enjoy regular updates and maintain security through the cloud.
  • IT Friendly: Easily deployable and connectable with internal IT resources, with accelerated upgrades. 
  • On-the-Go Information: Stay connected to data through its native mobile app and browser-accessible platform.
  • Strong Vendor Support: The vendor has earned several awards in recent years for its dedication to customer success through professional and friendly service.
  • Free Trial: Request a free 14-day trial of the product through the vendor’s website.
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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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  • App Studio: Develop customized applications called InfoApps that analyze data and generate insights for end-users. Supported features include data visualization, reporting, drill-downs and more. 
  • Data Visualization: Turn data into content with eye-catching data visualizations. Create and customize a variety of charts that highlight meaningful trends.
  • Pages: Organize visual content and information into interactive, responsive pages that function as dashboards. Drag and drop items onto the canvas and create compelling data stories 
  • BI Portal: Build a complete, modern website that displays key information in one place with zero-training accessibility. Encourage self-service data discovery through drill-down, filters and more. Enable a custom sign-in page for the company.
  • Home Page: Easily navigate to the tools, functions and features used most, with a personalized landing page that displays favorites, last viewed items and more, based on recent activity.
  • Data Management: Streamline data access and data management. Connect to various data sources — including big data — upload and modify files and prepare it for future analysis, all from a single environment. Improves data quality with various data preparation enhancements.
  • Reporting: Create highly complex reports from any enterprise data source. Automate scheduled report distribution to anyone within or outside the organization.
  • In-Document Analysis: Interact with analytics with an integrated, in-document engine that supports data sets and functions similar to Excel. Brought together in singular HTML 5 pages that are accessible even without an internet connection. 
  • Security: Leverage a variety of tools and controls for administering and securing the platform, including role-based access control and granular level security options.
  • Mobile: Run reports, analyses and dashboards from any corporate data source on iOS and Android devices. The native mobile app supports familiar, touch-based gestures for smooth navigation. Find, retrieve and share content, whether online or offline.
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Product Ranking

#1

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#50

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User Sentiment Summary

Great User Sentiment 474 reviews
Great User Sentiment 439 reviews
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.

87%
of users recommend this product

WebFOCUS has a 'great' User Satisfaction Rating of 87% when considering 439 user reviews from 5 recognized software review sites.

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4.5 (14)
4.3 (101)
4.4 (158)
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4.5 (170)
4.3 (244)
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4.3 (65)
4.2 (129)
3.2 (32)

Synopsis of User Ratings and Reviews

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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Support: All of the users who mentioned the vendor’s support praised their responsive, helpful support team and dedication to customer success.
Reporting: Around 96% of users who mentioned reporting said that this tool works well for report creation and scheduled distribution.
Data Visualization: About 90% of users who reviewed the tool for data visualization said that it excels in dashboard and chart creation.
Functionality: This is a robust, feature-rich tool with a great degree of flexibility and frequent updates, according to around 76% of users who reviewed the tool’s functionality.
Ease of Use: According to about 63% of users who reviewed the platform’s ease of use, its intuitive drop-and-drop interface simplifies data analysis and visualization.
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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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User Interface: Of the users who mentioned this solution’s UI, approximately 87% said that it looks outdated, especially compared to those of competitors.
Cost: About 83% of users who reviewed it for price said that this solution is expensive, especially when considering add-on modules.
Performance: All of the users who reviewed the platform’s performance and speed mentioned bugs, lag and crashes, among other issues.
Learning Curve: It takes some time to learn this platform, according to about 60% of users who reviewed its learning curve.
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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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WebFOCUS offers a feature-rich business intelligence data and analytics platform that unlocks actionable insights and the power of decision-making for users throughout an organization. Rated highly for ease of use by most reviewers, it empowers self-service data discovery with a user-friendly UI that enables drag-and-drop data analysis and visualization; some users noted that this UI looks outdated, especially compared to those of competitors. The platform offers a wide range of prebuilt data visualizations that users can further customize if necessary. This platform excels at creating and designing reports, then distributing them either at-will or through the automated scheduling tool, as noted by a majority of users who reviewed reporting. Most notably, the platform has an outstanding support team - all of the users who reviewed its support expressed satisfaction with their proactive, responsive assistance, citing the vendor’s dedication to the success of their customers as notably apparent. Customers can tailor the platform to their needs, as its flexibility allows for customized solutions. Frequent updates add value over time, though some users remarked that these sometimes break features from older versions. Other performance issues noted in reviews include lags when performing complex queries, infrequent crashes, slow load times and issues when accessing the platform from specific devices or browsers. While easy to pick up and use, especially for the end-user, some reviewers said that there is a learning curve to master the many features of this tool — a few users noted that this learning curve lasted a few months for some team members in their organizations. Overall, WebFOCUS is a worthy pick for self-service data visualization and reporting, especially in the hands of an organization willing to invest the resources and time to make it shine.

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