Cloudera vs GraphPad Prism

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Our analysts compared Cloudera vs GraphPad Prism based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

Cloudera Software Tool

Product Basics

Cloudera is a multi-environment analytics platform powered by integrated open source technologies that help users glean actionable business insights from their data, wherever it lives. With an enterprise data cloud, it puts data management at analysts’ fingertips, with the scalability and elasticity to manage any workload. It offers users transparency into the whole data lifecycle and the flexibility of customization through its open architecture.

It is available on an annual subscription basis with three offerings: CDP Data Center, Enterprise Data Hub and HDP Enterprise Plus. Each edition offers different components and pricing varies based on computing power, storage space and number of nodes.

The company merged with Hortonworks in 2019 to provide a comprehensive, end-to-end hybrid and multi-cloud offering.
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Graphpad Prism is a statistics, data analysis and graphing package that simplifies powerful statistics to help users analyze smarter, not harder. Though specialized for scientific research, it doesn’t require its users to have programming knowledge in order to tell stories with their data and create a wide variety of data visualizations with ease.

It can be installed on Windows or Mac devices and is available through a group or personal subscription, which comes with free updates during the subscription term and is billed on an annual basis, or through a perpetual license, which does not include upgrades and guaranteed support for future operating system updates. For short-term projects, individual users can get a monthly subscription. Students can receive a subscription at a discounted rate.
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$833/User, Annually
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$142 Annually
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Tailored to your specific needs
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Knowledge Base
24/7 Live Support
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Product Insights

  • Provides Data-Driven Insights: Make data-informed business decisions that boost efficiency, decrease risk and provide new insights. Features data discovery, analysis and interpretation tools necessary for businesses to make the right choices with confidence.
  • Industrialized AI: Takes an “AI factory” approach to BI and makes enterprise machine learning and artificial intelligence processes automated, repeatable and predictable, speeding up the time needed to go from numbers to outcomes.
  • Eliminates Silos: Move away from costly and inefficient data silos with a unified platform that performs a range of data analysis tasks simultaneously on the same data, right at the source. Speed up the data discovery process and improve productivity for the organization as a whole.
  • Capitalize on the Wealth of IoT: Contribute to overall business transparency by processing and integrating data from a huge reservoir of devices connected to the Internet of Things. Connects the information from these devices to its AI, which can monitor performance in real time, identify areas for improvement, reduce machine failure and improve overall ROI.
  • Secure by Design: Set up encryption across environments, ensuring consistent protocols and granular security policies across the platform. Built-in enterprise-grade auditing and lineage tracking capabilities provide comprehensive data governance to organizations.
  • Maximizes Interoperability: Ensures compatibility with all vendors through its 100% open-source architecture, and unlocks additional possibilities for enterprises. 
  • Deployable Anywhere: Safeguard and future-proof the company’s investment in BI. Stay immune to the cloud infrastructure battle with a single data management platform portable and flexible enough to move to and from the cloud as necessary. 
  • Scalability: Manage cloud costs and scale resources automatically as workloads increase, or scale down as demand falls, utilizing and paying for exactly how much is necessary.
  • Protects Your Business: Offers advanced behavior analytics, quick anomaly detection and visibility into every dimension of the enterprise. Protect data at all times with the assistance of both time-series and real-time threat analytics.
  • Free Trial: Sign up for a free 60-day trial of Cloudera Enterprise and many of its modules from the vendor’s website.
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  • Perform the Right Analysis: With clear language and a checklist for each process, Prism helps users select the most suitable statistical analysis from its library while bypassing technical jargon.
  • Helps You Learn As You Go: At almost every step, users can access pages from Prism’s online help. Tutorial data sets help users understand how and why they should perform analyses, how to make graphs and how to interpret the results of their analyses.
  • Focus on Research: Because users can utilize the software and automate processes without coding, it allows them to spend more time researching and less time programming. The software also takes care of updating graphs and results, freeing up even more time for researchers.
  • Publish with Ease: The solution allows users to customize and save default settings to meet their publishing requirements so that they can export publication-quality graphics with one click.
  • Enhance Collaboration: All parts of a Prism project, including the raw data, analyses, results, graphs and layouts, are contained in a single file that users can share with others, who can then follow their work step-by-step and add value to their findings.
  • Educational Resources and Support: Graphpad provides extensive online help guides for doing statistical analyses with Prism, as well as video tutorials and sample data sets that users can practice analyzing with the platform. The vendor also provides online training center options and technical support for the product, offering users the assistance and tools they need to succeed.
  • Free Trial: Interested parties can try the platform with a free 30-day trial with no credit card or commitment necessary.
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  • Data Science Workbench: Through a unified workflow, collaboratively experiment with data, share research between teams and get straight to production without having to recode. Create and deploy custom machine learning models and reproduce them confidently and consistently.
  • Real-Time Streaming Analytics: With edge-to-enterprise governance, Cloudera DataFlow continuously ingests, prioritizes and analyzes data for actionable insights in real-time. Develop workflows to move data from on-premises to the cloud or vice-versa, and monitor edge applications and streaming sources.
  • Machine Learning: Enable enterprise data science in the cloud with self-service access to governed data. Deploys machine learning workspaces with adjustable auto-suspending resource consumption guardrails that can provide end-to-end machine learning tools in one cohesive environment.
  • Data Warehouse: Merges data from unstructured, structured and edge sources. The auto-scaling data warehouse returns queries almost instantly and has an optimized infrastructure that moves workloads across platforms to prepare vast amounts of data for analysis.
  • Operational Database: The operational database promises both high concurrency and low latency, processing large loads of data simultaneously without delay. It can extract real-time insights and enable scalable data-driven applications. 
  • Open-Source Platform: Access the Apache-based source code for the program and make adjustments, customizations and updates as desired. 
  • Data Security and Governance: Reduce risk by setting data security and governance policies. The Cloudera Shared Data Experience (SDX) then automatically enforces these protocols across the entire platform, ensuring sensitive information consistently remains secure without disruption to business processes.
  • Hybrid Deployment: Leverage the deployment flexibility and accessibility to work on data wherever it lives. Read and write directly to cloud or on-premises storage environments. With a hybrid cloud-based architecture, choose between a PaaS offering or opt for more control via IaaS, private cloud, multi-cloud or on-premises deployment.
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  • Statistical Analysis: Prism offers a comprehensive library of statistical analyses, including nonlinear regression, t-tests, nonparametric comparisons, ANOVA, analysis of contingency tables, survival analysis and more. Users can confirm that they have chosen the appropriate test for their needs with a checklist that helps them understand the required statistical assumptions.
  • One-Click Regression Analysis: Prism allows users to select an equation and it will take care of the rest, including fitting the curve, displaying a table of results and function parameters, drawing the curve and interpolating unknown values.
  • Data Tables: Unlike spreadsheets or many other graphing programs, Prism has eight types of data tables that are specifically formatted for certain analyses, making it easier for users to enter data correctly and perform accurate analyses.
  • Real-Time Updates: When any changes are made to the data and analyses, those changes are reflected in the results, graphs and layouts instantaneously with updates in real time.
  • Customizable Data Visualization: Users can create a wide variety of visual representations of their data, including violin plots, box-whisker, bar graphs, subcolumn graphs, smoothing splines, scatter plots and more. They can also enhance these graphics with customization options that help them tell their data’s story in whatever way they desire; they can choose the type of graph, how the data is arranged, the style of the data points, labels, colors, fonts, look and more.
  • Prism Magic: Users can select one or more Prism graphs and apply a consistent look to the set with one-click simplicity, saving valuable time spent otherwise on standardizing the look of multiple graphics. 
  • Export Graphics: Users can export their graphs in high-quality and customize the file type, resolution, transparency, dimensions, color, space, etc. of their visualizations to meet the requirements of publication. To save time in the future, users can set their default export preferences.
  • Work Automation: Users can reduce the number of tedious steps needed to analyze data by setting up reproducible workflows that can create templates, duplicate families or clone graphs.
  • Tools for Teamwork: Prism allows for enhanced collaboration with other scientists, with all the information in a Prism project, including raw data, analyses, results, graphs and layouts, contained in a single, shareable file. Others can follow along with your work at every step, adding their insight and streamlining your collective research efforts.
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Product Ranking

#72

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#70

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User Sentiment Summary

Great User Sentiment 216 reviews
Excellent User Sentiment 202 reviews
82%
of users recommend this product

Cloudera has a 'great' User Satisfaction Rating of 82% when considering 216 user reviews from 4 recognized software review sites.

93%
of users recommend this product

GraphPad Prism has a 'excellent' User Satisfaction Rating of 93% when considering 202 user reviews from 3 recognized software review sites.

4.0 (26)
4.6 (51)
4.2 (5)
4.7 (143)
4.3 (144)
n/a
3.4 (41)
4.1 (8)

Awards

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

User Favorite Award

Synopsis of User Ratings and Reviews

Scalability: Cloudera can handle massive datasets and complex queries, making it suitable for large-scale data analysis and reporting.
Security: Cloudera offers robust security features, including data encryption and access control, ensuring sensitive data is protected.
Performance: Cloudera's optimized architecture and distributed processing capabilities deliver fast query execution and efficient data processing.
Integration: Cloudera integrates seamlessly with various data sources and tools, enabling users to connect and analyze data from different systems.
Community Support: Cloudera has a large and active community, providing access to resources, support, and best practices.
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Easy Data Entry: Users appreciate the intuitive interface that makes it simple to input and organize data, even for complex experiments. For example, users can easily import data from spreadsheets or directly enter data into the program.
Powerful Analysis: Prism offers a wide range of statistical tests and graphing options, allowing users to analyze data in depth and visualize results effectively. For example, users can perform t-tests, ANOVA, regression analysis, and more.
Customization: Users can customize graphs and reports to meet their specific needs, ensuring that data is presented clearly and effectively. For example, users can adjust colors, fonts, and labels to create visually appealing and informative graphs.
Collaboration: Prism allows users to share data and results with colleagues, facilitating collaboration and communication. For example, users can export data and graphs in various formats, including PDF, Excel, and PowerPoint.
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Steep Learning Curve: New users often find Cloudera's interface and complex architecture challenging to navigate, requiring significant time and effort to master. This can be especially problematic for teams with limited technical expertise.
Costly Implementation: Cloudera's pricing model can be expensive, particularly for large deployments. The cost of hardware, software licenses, and ongoing support can be a significant barrier for some organizations.
Limited Scalability: While Cloudera offers scalability, some users have reported challenges scaling their deployments to meet rapidly growing data volumes. This can lead to performance bottlenecks and slow query execution times.
Complex Management: Managing a Cloudera cluster can be complex, requiring specialized skills and knowledge. This can be a burden for organizations with limited IT resources.
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Steep Learning Curve: New users often find the interface and features overwhelming, requiring significant time investment to master. This can be a major hurdle for teams with tight deadlines or limited training resources.
Limited Data Handling: Prism struggles with large datasets, making it less suitable for complex analyses involving extensive data manipulation or integration with other tools. This can be a problem for businesses with large-scale data collection and analysis needs.
Lack of Collaboration Features: Prism lacks robust collaboration features, making it difficult for teams to work together on projects. This can be a significant drawback for businesses that rely on collaborative data analysis and reporting.
Costly Licensing: Prism's licensing model can be expensive, especially for larger teams or organizations. This can be a barrier for businesses with limited budgets or those looking for more cost-effective solutions.
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Is Cloudera the answer to your data management woes, or is it just a bunch of hot air? User reviews from the past year paint a mixed picture of Cloudera. While some users praise its flexibility and ability to handle large datasets, others find it cumbersome and expensive. Cloudera's hybrid cloud approach, allowing users to deploy on-premises or in the cloud, is a major selling point for many. However, some users find the platform's complexity a barrier to entry, especially for those without extensive experience in data management. Cloudera's integration with other tools, such as Apache Hadoop, is a key differentiator, but some users report issues with compatibility and performance. Cloudera is best suited for large enterprises with complex data needs and a dedicated team of data engineers. Its robust features and scalability make it a powerful tool for organizations that require a comprehensive data management solution. However, smaller businesses or those with limited technical resources may find Cloudera's complexity and cost prohibitive.

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Is GraphPad Prism the real deal or just a statistical mirage? GraphPad Prism is a popular software choice for scientists who need to analyze and visualize their data. Users praise its ease of use, especially for those without a strong statistics background. They appreciate the intuitive interface and the clear explanations provided for each statistical test. The software's ability to generate publication-quality graphs is a major selling point, with users highlighting the wide range of customization options available. For example, one user mentioned using Prism to generate figures for publication in peer-reviewed journals, highlighting its ability to create professional-looking visuals. However, some users have expressed concerns about the software's performance, particularly on older or less powerful computers. One user noted that Prism can be resource-intensive, even on a computer with 8GB of RAM. This can be a significant drawback for researchers who need to analyze large datasets or work on machines with limited resources. Additionally, some users have suggested that the tutorials could be improved, particularly for specific analyses like IC50 calculations. They believe that more real-life examples and detailed explanations would be beneficial. Overall, GraphPad Prism is a powerful tool for scientists who need to analyze and visualize their data. Its ease of use, comprehensive statistical analysis capabilities, and ability to create publication-quality graphs make it a strong choice for researchers. However, its performance on older computers and the potential for improvement in its tutorials are areas that could be addressed in future updates. GraphPad Prism is most suited for scientists who are looking for a user-friendly software that can handle a wide range of statistical analyses and produce high-quality graphs for publications.

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