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Cloudera vs Oracle Analytics Cloud

Last Updated: November 18th, 2024

Our analysts compared Cloudera vs Oracle Analytics Cloud 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.

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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.

Oracle Analytics Cloud is a public cloud service on which you can build and run reporting and analytics solutions. It can also manage data from Oracle Database and Oracle Autonomous Data Warehouse. Pairing it with Oracle Data Integration can help you move and transform data at scale. But that’s not all. You can build and deploy analytics applications even with non-Oracle systems. However, the level of integration and capabilities may differ.

You’ll need an Oracle Cloud account, and a free trial is available. Oracle customizes the view for you, whether you’re a web app developer, account admin or cloud architect. Workbooks and dashboards enable data exploration. You can set it up so the system sends reports to selected users on schedule. Governed analytics is available; your data stays secure. Annotations, export options and integration with social platforms are other capabilities.

Two pricing tiers are available. The Professional edition has self-serve analytics, direct source connections and dataflows for preparing content. It costs $16 per user monthly.

The Enterprise edition lets you enrich data, connect to private sources and build semantic models. You can track usage and set encryption keys, all at a cost of $80 per user monthly. Opt for a user or consumption model based on OCPUs (Oracle CPUs).

The user reviews were an interesting read. I haven’t seen many products with such strongly divided opinions. In all positive reviews, over 70% of the users voted for a specific feature, indicating a high level of user satisfaction and perceived value. On the flip side, over 87% of users said price and a steep learning curve were blockers to successful adoption.

$833/User, Annually

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$16/User, Monthly

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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.

Leverage ML: According to our research, Oracle Analytics Cloud gets the top score of 76 for augmented analytics. The Explain and AutoML functionalities and one-click predictions give it an edge over other competitors like Qlik Sense and
Generate Reports: Oracle Analytics Cloud scores 93 in our analyst rankings with instant and planned reports that are interactive and accept conditional formatting. Plus, it supports text and voice searches even on the mobile app.
Monitor Usage: Track expenses with the Billing tab on the Oracle Cloud Console. Keep tabs on usage with a dedicated tool, Oracle Cost Analysis, included with your Oracle Cloud subscription.
Try for Free: Sign up for a free Oracle Cloud trial and get access to the Autonomous Database and Object Storage. You’ll need to sign in with your credit card details. The vendor deducts a token account verification amount from your card, which they return promptly. For me, it was annoying as they deducted it again three days later. Get $300 credits for 30 days to use the Analytics Cloud, Data Integration and the Container Engine for Kubernetes.

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.

Deployment: Install and run anywhere, including as a hybrid solution. Scale the instance depending on your workload — deploy OCPUs in multiples of two, extending up to 52. Or pause it when idle. Though identity management is available, there is the option to use one’s own SSO provider. Admins can set user, group and role-based permissions.
Connectivity: Make decisions based on data; connect to social media feeds, data lakes and IoT sources. Store and process data at scale, irrespective of its volume, velocity and variety. Get started as soon as you log in with over 40 readymade connectors.
Direct Query: Oracle Analytics Cloud uses live queries and data caching to fetch responses. Each has its downside. Live connections are heavier on the system, and you might have to compromise on data freshness with data caching. A combination of both might be best. Consider live queries for critical KPIs and data caching for less frequent queries.
Data Preparation: Enrich data from the interface — get data quality insights as you work. Remove the grunt work — create reusable flows for transforming data you can test, share and schedule. Add custom calculations or write regular expressions in the dataset editor.
Semantic Data Modeling: Engage business, dev and data teams in meaningful discussions. Give them data views with a presentation layer that simplifies metrics. Hide the physical data structure with a logical one that speaks the business language. Give stakeholders the power to explore data independently.
AI/ML: Boost productivity with embedded machine learning and natural language insights every step of the way. Display quick forecasts, trend lines and clusters from a popup menu with one click. View the basic facts, key drivers and anomalies with the Explain option. Hit the ground running with recommendations on dimensions, measures and attributes to use when you don’t know where to start.
Oracle Analytics Publisher: Generate reports from any dataset or semantic model. Create formatted documents unique to your business, be it shipping labels, checks, letters or PDF forms.
Data Visualizations: Put your best foot forward with suitable charts and graphs that convey your message effectively. Modify them to answer users’ questions better. Choose from over 45 visualization types, or build your own using extensions from its vast library.
Embedded AI On Mobile: Get real-time alerts and intelligent recommendations on mobile. The Oracle Analytics mobile app captures your preferences and location. Upload datasets just like on the desktop or create a workbook from existing data. Powerful searches enable access to your favorite worksheets; add them to your home screen for a quick view. Use voice-enabled searches and listen to the results as a podcast.

Product Ranking

#72

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#10

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Analyst Rating Summary

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User Sentiment Summary

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.

84%

of users recommend this product

Oracle Analytics Cloud has a 'great' User Satisfaction Rating of 84% when considering 719 user reviews from 4 recognized software review sites.

4.0 (26)

4.0 (228)

4.2 (5)

4.1 (59)

4.3 (144)

4.3 (316)

3.4 (41)

4.3 (116)

Awards

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.

User-Friendly: Citing its interface, about 91% of users agreed that a drag-and-drop UI makes it easy to use.

Machine Learning: Around 86% of users who discussed augmented analytics were impressed with its ML capabilities.

Integrations: Approximately 84% of users who mentioned connectivity said the platform worked well with other systems, especially Oracle products.

Functionality: According to 83% of users who reviewed capabilities, it has all the required features to support data tasks.

Data Visualization: Around 73% of users who mentioned visualization praised the platform for its storytelling features.

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.

Price: About 88% of reviews citing pricing said that it’s too expensive.

Adoption: Approximately 87% of users who discussed onboarding said there’s a significant learning curve.

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.

Oracle Analytics Cloud is among the vendor’s many data services, including a business intelligence suite and a data intelligence platform. Besides, Oracle offers bespoke solutions for HCM, supply chain and customer experience. What differentiates Oracle Analytics is that extra dash of augmented capabilities.Embedded BI is where it truly shines, giving you natural language insights with a single click. This feature extends to its mobile app, and it outperforms many leading platforms with natural language queries and podcasts on mobile.According to our researchers, Oracle Analytics Cloud has fewer out-of-the-box features than its competitors, such as Power BI and Qlik Sense. Plus, licensing becomes complex when combining the database, middleware and analytics applications.It’s common for large vendors to offer specialized platforms, but the downside is that they can be out of reach of small organizations. But there’s a silver lining. Many vendors offer customized solutions, so we advise reaching out to the vendor for quotes.Users appreciate its regular updates, but some report initial bugs due to its relative newness. Despite a positive user experience, the learning curve can be steep. Some users found technical support slow and inadequate, as did I. They took two business days to get back to me when I needed assistance with my account.Oracle Analytics, though a robust platform, is suitable for mid- and large organizations. If you seek a powerful, scalable platform, consider opting for a trial, but be prepared for sticker shock, especially if you’re new to the Oracle ecosystem.

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FAQ

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