Top Hadoop Alternatives & Competitors For 2024

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Looking for alternatives to Hadoop? Many users crave user-friendly and feature-rich solutions for tasks like Dashboarding and Data Visualization, Data Management, and Machine Learning. Leveraging crowdsourced data from over 1,000 real Big Data Analytics Tools selection projects based on 400+ capabilities, we present a comparison of Hadoop to leading industry alternatives like WebFOCUS, BigQuery, MATLAB, and Looker Studio.

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  • UI may feel outdated to some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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BigQuery, a cloud-based data warehouse offered by Google, provides businesses with a scalable and cost-effective solution for analyzing massive datasets. It eliminates the need for infrastructure management, allowing users to focus on extracting valuable insights from their data using familiar SQL and built-in machine learning capabilities. BigQuery's serverless architecture enables efficient scaling, allowing you to query terabytes of data in seconds and petabytes in minutes.

BigQuery is particularly well-suited for organizations dealing with large and complex datasets that require rapid analysis. Its ability to integrate data from various sources, including Google Cloud Platform and other cloud providers, makes it a versatile tool for businesses with diverse data landscapes. Key benefits include scalability, ease of use, and cost-effectiveness. BigQuery offers a pay-as-you-go pricing model, allowing you to only pay for the resources you consume. You are billed based on the amount of data processed by your queries and the amount of data stored.

While BigQuery offers numerous advantages, it's important to consider factors such as your specific data analytics needs and budget when comparing it to similar products. User experiences with BigQuery have generally been positive, highlighting its speed, scalability, and ease of use. However, some users have noted that the pricing structure can become complex for highly demanding workloads.

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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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Google Looker Studio is a robust data analytics and business intelligence platform designed to help organizations extract valuable insights from their data. It offers a user-friendly interface for data exploration, powerful visualization tools, and real-time data monitoring. Key features include customizable dashboards, SQL-based queries, and seamless data integration from various sources. Users can collaborate within the platform, fostering a data-driven culture. Looker Studio empowers users to make data-informed decisions, with the ability to create tailored reports and leverage machine learning for predictive analytics. It suits businesses of all sizes and industries, facilitating scalable analytics and promoting data-driven decision-making.
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Product Assistance

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Product Ranking

#1

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#50

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#10

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#11

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#22

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Big Data Analytics Tools

Find out who the leaders are

Analyst Rating Summary

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Availability and Scalability
Computer Vision and Internet of Things (IoT)
Dashboarding and Data Visualization
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Geospatial Visualizations and Analysis
Availability and Scalability
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Platform Security
Reporting
Dashboarding and Data Visualization

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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WebFOCUS
BigQuery
MATLAB
Looker Studio
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Augmented Analytics Computer Vision and Internet of Things (IoT) Dashboarding and Data Visualization Data Management Data Preparation Geospatial Visualizations and Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 38 0 94 74 74 55 65 100 0 25 50 75 100
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User Sentiment Summary

Great User Sentiment 474 reviews
Great User Sentiment 439 reviews
Excellent User Sentiment 724 reviews
Excellent User Sentiment 4535 reviews
Great User Sentiment 1074 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.

90%
of users recommend this product

BigQuery has a 'excellent' User Satisfaction Rating of 90% when considering 724 user reviews from 3 recognized software review sites.

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.

86%
of users recommend this product

Looker Studio has a 'great' User Satisfaction Rating of 86% when considering 1074 user reviews from 3 recognized software review sites.

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Awards

we're gathering data
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User Favorite Award
User Favorite Award
Reporting Award

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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Performance: The system can execute queries on massive amounts of data with agility, as specified by about 89% of users who mentioned performance.
Functionality: About 68% of users who reviewed functionality talked about its robust inbuilt features.
Ease of Use: The UI is simple and easy to navigate, according to about 72% of users who talked about user-friendliness.
Integration: Approximately 75% of reviewers who talked about integration said that it connects to numerous other tools seamlessly.
Scalability: All users who reviewed scalability said that the platform scales to thousands of servers.
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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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Intuitive Interface: Users appreciate Looker Studio's user-friendly interface, making it easy to navigate and perform data analysis tasks.
Powerful Visualization: The platform offers a wide range of visualization options, enhancing data presentation and making insights more accessible.
Collaborative Tools: Users value the collaborative features, enabling teams to work together seamlessly, share insights, and drive data-driven decisions.
Real-Time Insights: Looker Studio's ability to provide real-time data insights helps users stay informed and agile in their decision-making processes.
Customization: Users can tailor dashboards and reports to their specific needs, allowing for a personalized analytics experience.
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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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Cost: Approximately 76% of users who mentioned cost complained that it’s expensive, and charges can rack up quickly if queries aren’t properly constructed.
Learning Curve: About 82% of users mentioned that the software has a steep learning curve.
Resources: About 89% of users who spoke about resources said that documentation and video tutorials are lacking and need improvement.
Visualization: Data visualization capabilities aren’t up to the mark, according to all users who talked about visualization.
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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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Steep Learning Curve: Some users find Looker Studio challenging to learn, especially if they lack SQL or data analysis skills, leading to initial difficulties.
Data Integration Complexity: Integrating data from various sources can be complex, requiring substantial setup and maintenance efforts for certain users.
Resource Intensiveness: Resource-intensive tasks, such as processing large datasets, may lead to performance issues, causing frustration for some users.
Costs: The pricing structure can be a drawback for organizations with tight budgets, as Looker Studio's pricing may not be suitable for all user needs.
Limited Offline Functionality: Some users desire more robust offline capabilities, as Looker Studio primarily operates in an online environment.
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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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Bigquery is a scalable big data warehouse solution. It enables users to pull correlated data streams using SQL like queries. Queries are executed fast regardless of the size of the datasets. It manages the dynamic distribution of workloads across computational clusters. The easy-to-navigate UI is robust and allows the user to create and execute machine learning models seamlessly. Users liked that it can connect to a variety of data analytics and visualization tools. However, users complained that query optimization is an additional hassle they have to deal with, as the solution is expensive and poorly constructed queries can quickly accumulate charges. It can be overwhelming for the non-technical user, and SQL coding knowledge is required to leverage its data analysis capabilities. Data visualization features are lacking and in need of improvement.

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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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User reviews for Google Looker Studio indicate both strengths and weaknesses. Many users praise its intuitive interface, which simplifies data analysis. The platform's powerful visualization tools and real-time insights are widely appreciated, enabling users to present and act on data effectively. Collaboration features also receive positive feedback, facilitating teamwork and informed decision-making. However, several users highlight challenges. A notable drawback is the steep learning curve, especially for those without SQL or data analysis skills. Some users find data integration complex and resource-intensive, potentially impacting performance. Cost considerations also arise, with users noting that Looker Studio's pricing may not align with all budgets. In comparison to similar products, Looker Studio stands out for its user-friendly interface and strong visualization capabilities. However, some users mention limitations in offline functionality, which competitors may handle better. Overall, Google Looker Studio appears to be a valuable tool for data analysis and collaboration, but it may require a learning curve and careful consideration of budget constraints.

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Related Categories

Top Alternatives in Big Data Analytics Tools


Alteryx

Azure Synapse Analytics

Dataiku

H2O.ai

IBM Watson Studio

KNIME

Looker Studio

Oracle Analytics Cloud

Qlik Sense

RapidMiner

SageMaker

SAP Analytics Cloud

SAS Viya

Spotfire

Tableau

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