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Cloudera vs SPSS Statistics

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Our analysts compared Cloudera vs SPSS Statistics 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
SPSS Statistics 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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IBM SPSS, or Statistical Product and Service Solutions, is a data analysis platform that provides advanced statistical insights to propel business decision-making and research by crunching large datasets. With a user-friendly interface, it empowers everyone from basic users to experienced data scientists to perform statistical analysis. Scalable and agile, it is suitable for companies of all sizes.

Users can purchase it through an on-premises license or a subscription plan to a hybrid SaaS. Users who choose either monthly or annual subscription receive access to the base version and can choose which of three optional add-ons to include, if any, between Custom Tables and Advanced Statistics, Complex Sampling and Testing, and Forecasting and Decision Trees.

Perpetual and term licensees can choose between four editions that offer different levels of functionality: Base, standard, professional and premium. It was first launched as Statistical Package for the Social Sciences by three Stanford students in 1968 and later acquired by IBM in 2009.
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$833/User, Annually
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Tailored to your specific needs
$99 Monthly
Free Trial is available →
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Tailored to your specific needs
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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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  • Increase Reliability of Analysis: Data analysts and scientists can reach more dependable conclusions and ensure high accuracy, backed by numbers and models made from their data.
  • Assists in Decision Making: Organize and analyze data sets in order to draw conclusions, glean insights and make data-driven business decisions.
  • Statistics with Speed: Maximize productivity by quickly crunching data sets. Handle complicated tasks in a third of the time of many non-statistical programs.
  • Data Management: Remove manual work, as the system does all the legwork in preparing and organizing data sets for analysis. It estimates and uncovers missing values, improving the accuracy of reports.
  • Ease of Use: According to the IBM website, 81% of reviewers rank SPSS as easy to use. A point-and-click interface and natural language processing allow analytics capabilities to be accessed by those without coding skills or advanced statistics knowledge.
  • Scalability: Built to scale and work with large volumes of data, supporting anything from basic descriptive analytics to advanced statistics simulations. Purchase as many licenses as needed, ensuring cost-efficiency for small businesses as well as robustness for large scale enterprises.
  • Customized Predictive Analytics: Tailor predictive analytics to unique needs and perform ad hoc analysis to find the information needed, making better predictions over time.
  • Free Trial: Access all capabilities with a free 14-day trial period.
  • Academic Versions: An academic version is optimized for higher education and research. Program availability varies based on user roles, including students, teachers, researchers and campus-wide administrators.
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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 Source Connectivity:  Enables reading and writing data from a wide spectrum of file formats and sources. These include ASCII text files, spreadsheets and databases like Microsoft Excel and Microsoft Access, as well as those from other statistics packages. 
  • Data Preparation: Streamlines the data preparation process. Identify invalid values, view patterns of missing data and automate data preparation to analyze and clean up large data sets in a single step. Validate the accuracy of analysis with a thorough, efficient data conditioning workflow. 
  • Point-and-Click Interface: Allows users without coding knowledge to leverage point-and-click data analysis with drop-down menus and drag-and-drop functionality. 
  • Automated Analytics: Automate common tasks with syntax and create customized data analyses that run using algorithms. 
  • Comprehensive Statistical Analysis: Perform many kinds of statistics tests, including but not limited to linear and non-linear models, simulation modeling, bayesian statistics, custom tables, complex sampling, advanced and descriptive statistics, and regression.
  • Ad Hoc Analysis: “Slice and dice” data by creating customized tables to dig deeper and improve understanding.
  • Predictive Analytics:
    •  Uncovers complex relationships between variables with functions like time series analysis, forecasting, neural networks and temporal causal modeling. 
    •  Simulates values and accounts for the uncertainty of the future using probability distributions. 
    •  Improves predictive models with multilayer perception and radial basis function. 
  • Geospatial Analysis: Explore the relationship between data points that can be tied to specific locations.
  • Direct Marketing: Improve campaigns and target key customers. Conduct advanced statistics analysis of customers or contacts with RFM (recency, frequency, monetary) analysis.
  • Open-Source Integration: Enhance syntax with programming languages R and Python through a library of more than 100 free extensions on the IBM Extension Hub, or opt to build programs.
  • Export with Ease: Export data to a proprietary file format. Can be exported to a variety of widely accessible formats such as text, Microsoft Word, PDF, Excel, HTML, XML, XLS and more. Export to a variety of graphic image formats.
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Product Ranking

#72

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#86

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User Sentiment Summary

Great User Sentiment 216 reviews
Great User Sentiment 1881 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.

87%
of users recommend this product

SPSS Statistics has a 'great' User Satisfaction Rating of 87% when considering 1881 user reviews from 6 recognized software review sites.

n/a
4.3 (18)
4.0 (26)
4.2 (712)
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4.51 (528)
4.2 (5)
4.5 (425)
4.3 (144)
4.6 (40)
3.4 (41)
4.2 (158)

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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Research Analysis: It’s easy to analyze and interpret large and complex datasets to generate insights, according to 96% of reviewers who mention this feature.
Ease of Use: The platform is user-friendly and easy to navigate as observed by almost 95% of reviewers mentioning ease of use.
Interface: The interface has a clean layout and visually appealing design according to 75% of users referencing it.
Syntax: It’s easy to use (copy and paste) and proof syntax, and save for later, as noted by 95% of reviewers who talk about this feature.
Resources: Of users mentioning support, 93% agreed that access to various support manuals and courses, as well as an extensive user community, was helpful.
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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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Learning Curve: It needs extensive learning to understand advanced tools and different aspects, as observed by almost 75% of reviewers mentioning training.
Cost: More than 90% of users referencing the price remarked that the product is a bit expensive.
Slow Operation: The system runs slow at times while using huge or complex data sets, and needs to restart, as observed by 92% of reviews on this topic.
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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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SPSS Statistics is a point-and-click data analysis software that allows non-technical users to leverage advanced statistical analysis. Users praised its user-friendly, visually appealing interface. Many reviews also appreciated how easy it is to use and proof syntax, along with the extensive help documentation available for better understanding. Despite its ease of use, a majority found that using advanced tools involved a steep learning curve. Additionally, its cost runs on the high side and processing large amounts of information slows down its performance, as observed by most reviewers. It’s a good fit for students, data scientists and companies that want to analyze data sets but don’t have the technical resources and expertise to use a more advanced tool.

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