RStudio vs Cloudera

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Our analysts compared RStudio vs Cloudera 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

RStudio is an integrated development environment suite for the R programming language, synthesizing coding tools into one software tool for easier advanced data processing. Using in-memory processing, it is capable of parsing big data through integrations and connections.

It is available in both open-source and commercial formats, with extra features available in the paid edition includes more sophisticated collaboration and security efforts. The free version is capable of end-to-end analytics, from API connectivity and data ingestion to visualization creation and distribution. It can be deployed standalone or on a web browser through connection to RStudio Server.
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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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$4,975 Annually
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$833/User, Annually
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Product Insights

  • Open-Source or Commercial: Create visualizations and reports from data analysis scripts with the open-source version. Access more advanced features, including deeper security and support with the paid version.
  • Streamlined R Programming: Execute code directly from the source editor by integrating the tools being used into one interface. Supports Git and Subversion for more advanced code writing needs.  
  • Advanced Data Analysis: Investigate trends on a big data scale via integrations for distributed processing, data modeling and predictive analysis. Develop deep analytical insights through R, the premier statistics coding language. 
  • Proprietary R Packages: Get sophisticated ready-to-install R packages comparable with machine learning frameworks to ingest, store, analyze and consume data.  
  • Data Visualization: Easily digest analyzed data through out-of-the-box and integrated visualizations and data consumption deployment vessels using Shiny and ggvis. Create interactive dashboards and charts with drill-down capabilities. 
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  • 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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  • Source Editor: Develop programs in a single console window by synthesizing and integrating all tools in use. Highlight syntax, define functions and complete code in the console.  
  • Web Applications: Publish applications, dashboards and documents to the web with the internally-developed Shiny Server R package. 
  • Flexdashboard: Develop interactive dashboards with JavaScript visualizations, with support for HTML widgets, with this R package. 
  • Launcher: Launch R and Python processes remotely or submit R scripts to compute clusters like SLURM or Kubernetes. 
  • REST API Creation: Develop web API connections with the plumber R package — with as little as a single line of code. 
  • Spark Integration: Integrate seamlessly with Apache Spark to achieve big data analytics through distributed processing and leverage its machine learning capabilities to run more advanced queries.  
  • RStudio Connect: Publish statistical data analyses in the form of visually impactful visualizations, synthesizing all the aforementioned publishing features into one interface.  
  • Data Modeling and Prediction: Powers predictive and prescriptive analytics via connectivity to TensorFlow. Improves the product’s own data modeling capabilities via Tidymodels R package. 
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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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Product Ranking

#20

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Business Intelligence Tools

#72

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Business Intelligence Tools

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User Sentiment Summary

Excellent User Sentiment 700 reviews
Great User Sentiment 216 reviews
90%
of users recommend this product

RStudio has a 'excellent' User Satisfaction Rating of 90% when considering 700 user reviews from 5 recognized software review sites.

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.

5.0 (12)
n/a
4.5 (485)
4.0 (26)
4.6 (89)
4.2 (5)
4.4 (43)
4.3 (144)
4.4 (71)
3.4 (41)

Awards

RStudio 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

Data analysis: Around 96% of users who reviewed data analysis said that the platform had strong machine learning and data analysis capabilities.
Functionality: Approximately 86% of users who mentioned functionality said that the tool had a wide range of powerful features for efficient data visualization and analysis.
Ease of Use: The interface was user-friendly and easily navigable, according to 74% of users who reviewed this feature.
Cost: About 93% of users who mentioned pricing said that the open source version of the platform was a definite plus.
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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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Performance: The tool used up a lot of memory and slowed down when processing large amounts of data, around 88% of users who mentioned its performance said.
Steep Learning Curve: Approximately 73% of users said that it was challenging to work with the platform without previous knowledge of R and that the syntax was difficult to learn.
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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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RStudio is a powerful web- and cloud-based BI platform with excellent statistical analysis and data science capabilities. Integrating with cloud computing technologies, the platform has good machine learning capabilities to power data analysis by providing a wide range of features for data recovery, presentation and interpretation. It provides rich built-in visualization libraries with pre-set charts and functions that drastically reduce the need to code. Many users who reviewed its UI said that the interface was user-friendly and easy to navigate, though some users said that it looked dated and could do with an upgrade. Quite a few users who reviewed the platform for data analysis said that it was easy to run statistical and regression tests with minimal coding, and coupled with an open-source server, this platform served their data needs well. On the flip side, many users who reviewed the tool for performance said that it consumes a lot of memory and lags behind its competitors in speed. Quite a lot of users mentioned that the platform could be buggy at times and was prone to crashes, possibly because some libraries were not optimized for performance with large datasets. Many users found it confusing to access the open-source version, especially since separate versions of the platform work differently with some library packages. Some users complained that the code run, once started, could not be stopped and the stop button on the interface didn’t work. A majority of users who reviewed the learning curve as a feature said that the help section was difficult to understand and previous knowledge of R was required to leverage the tool to its fullest. In summary, RStudio is a versatile and extensible BI tool powered by machine learning and is capable of insightful statistical data analysis and forecasting capabilities.

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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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