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Cloudera vs NVivo

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Our analysts compared Cloudera vs NVivo 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.

Overview Pricing Benefits & Features User Ratings Analyst Summary Screenshots
Cloudera Software Tool
NVivo Software Tool
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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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NVivo is a qualitative data analysis solution for academic and industrial research. It lets users code and visualize their findings from interviews, surveys, text documents and demographic information. It’s helpful in social sciences, education and healthcare.

It has a friendly interface, powerful searches and advanced graphics. Once set up, the system can perform automatic sentiment analysis. Users can record the coding schemes and use them across the data. Documenting the steps enables future researchers to validate the research.

The vendor offers exclusive modules for collaboration and transcription. Its Collaboration Cloud lets many people work on the same project.

Pros
  • Powerful data management
  • Rich coding and query tools
  • Visualizations and data exploration
  • Team collaboration features
  • Support for various data formats
Cons
  • Steep learning curve
  • Can be expensive for individuals
  • Limited free trial/demo
  • Not ideal for simple projects
  • Occasional bugs and glitches
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$833/User, Annually
Free Trial is available →
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Tailored to your specific needs
$99/User, Monthly
Free Trial is available →
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Tailored to your specific needs
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Android
Chromebook
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Linux
Android
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Cloud
On-Premise
Mobile
Cloud
On-Premise
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Product Assistance

Documentation
In Person
Live Online
Videos
Webinars
Documentation
In Person
Live Online
Videos
Webinars
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support

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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  • Boost ROI: Tap into buyer sentiment by noting their needs and preferences and applying them to product development. Push sales by fine-tuning marketing campaigns.
  • Innovate: Launch new products and improve existing offerings. Go beyond numbers and discover what customers think and feel with thematic and sentiment analysis.
  • Act: Save time while searching for information. Organize data from various sources, such as interviews, surveys and social media, in one system.
  • Improve Services: Build stronger customer associations by serving them better. Identify their pain points and improvement areas by analyzing feedback.
  • Save Money: Free resources for more strategic work by automating tasks like transcription — auto-code interviews with NVivo 14.
  • Test Drive: Try it for 14 days free, including the Collaboration Cloud.
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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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  • Data Import: Pull data from mobile apps like Evernote and organize it using folders, sets or file classifications. It supports transcripts, articles, audio/video recordings and social media content.
  • Qualitative Analysis: Uncover hidden insights using powerful search tools. It turns interviews, surveys and documents into charts, word clouds and maps.
  • Thematic Analysis: Understand findings after digging deep into gathered data and spot emerging themes.
  • Integrations: Combine research materials in one place. Allows direct imports from Microsoft Office. Plus, it can use data from SurveyMonkey and social media platforms.
  • Sharing and Publishing: Export results, models and charts to various formats, including Excel, Word, text, rich-text and PDF files. Use the system clipboard to copy and paste graphics into reports and presentations.
  • Transcription: Review and edit transcripts, tag speakers, and add notes, then import transcripts directly into NVivo for analysis. NVivo Transcription auto-transcribes uploaded audio files, with support for 28 languages.
  • Multilingual Options: Analyze data in Chinese, Japanese, English, French, German and Portuguese, among other languages.
  • Collaboration Cloud: Work together to co-author research projects. A user uploads a master project to a secure cloud workspace, enabling others to download and work on it offline and then seamlessly merge their edits back into the main project.
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Product Ranking

#72

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#42

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Business Intelligence Tools

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User Sentiment Summary

Great User Sentiment 216 reviews
Great User Sentiment 179 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.

82%
of users recommend this product

NVivo has a 'great' User Satisfaction Rating of 82% when considering 179 user reviews from 2 recognized software review sites.

4.0 (26)
4.1 (133)
4.2 (5)
4.1 (46)
4.3 (144)
n/a
3.4 (41)
n/a

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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Data Management: Organize and store various data types (text, audio, video, images) in one secure location.
Flexible Coding: Employ diverse coding approaches (tree, auto and query) to categorize and analyze data based on research questions.
Relationship Exploration: Uncover connections and hierarchies between codes using visual network maps and relationship coding.
Advanced Querying: Search coded data for specific terms, patterns or code combinations to identify key themes and trends.
Visualizations: Generate various visualizations (word clouds and concept maps) to present complex data findings clearly.
Collaboration: Share and collaborate on projects with other researchers using cloud-based options or file exports (depending on the version).
Support & Resources: Benefit from extensive online resources, tutorials, and user communities for troubleshooting and learning best practices.
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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 report difficulty in mastering NVivo's features quickly, which impacts their productivity and project timelines.
High Cost: Some users find NVivo's pricing to be prohibitive, particularly those from smaller institutions or independent researchers with limited budgets.
Limited Cross-Platform Support: NVivo's limited compatibility with non-Windows operating systems can be a barrier for Mac or Linux users, who may have to seek alternatives or use virtual machines.
Resource Intensiveness: NVivo can be demanding on computer resources, leading to performance issues on less powerful machines, which can frustrate users when handling large data sets.
Occasional Software Bugs: Users occasionally encounter bugs that can disrupt workflow and require waiting for patches or updates, affecting the software’s dependability.
Rigid Licensing Policy: NVivo's licenses can be inflexible, and transferring a license to another computer can be problematic, causing inconvenience to users who need mobility.
Complex Data Importation: Some users find importing data from various sources into NVivo cumbersome, which could lead to a time-consuming setup process.
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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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NVivo is qualitative data analysis software that received positive reviews from users. They appreciate its user-friendly interface, powerful features and ability to handle large datasets.However, some users complained about lax customer support and the occasional bug.NVivo is popular but not as robust as some of the other options. It’s also expensive. However, many users believe that the extra cost is worth it for the additional features and functionality. It has robust coding features to analyze large amounts of data quickly.Overall, NVivo is a user-friendly qualitative data analysis software that can be expensive and complex for individual users but is a handy assistant for teams.

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