Oracle Analytics Cloud

Basic Information

• Model: Oracle Analytics Cloud (OAC)
• Version: Oracle Analytics Cloud receives continuous updates. Recent updates include January 2025 and May 2025, bringing enhancements in AI, video analytics, connectivity, and user experience.
• Release Date: Oracle Analytics Cloud was initially made available on November 5, 2019.
• Minimum Requirements: As a cloud service, OAC's core infrastructure requirements are managed by Oracle. Client-side tools and data gateways have specific OS requirements.
• Supported Operating Systems: For client tools like Oracle Data Gateway, supported operating systems include Oracle Linux (6 Update Level 6+, 7 Update Level 0+, 8 Update Level 0+), Red Hat Enterprise Linux (6 Update Level 6+, 7 Update Level 0+, 8 Update Level 0+), SLES (11 Service Pack 3+, 12 Service Pack 1+), and Microsoft Windows x64 (7 SP1+, 8.1, 10, 11; Windows Server 2012 R2, 2016, 2019).
• Latest Stable Version: OAC operates on a continuous update cycle, with new features and enhancements released regularly. For example, the May 2025 update introduced significant improvements.
• End of Support Date: Oracle Analytics Cloud, as a continuously updated cloud service, does not typically have a fixed "end of support" date in the traditional sense for on-premises software. Support is ongoing as long as the subscription is active.
• End of Life Date: Not applicable for a continuously updated cloud service.
• License Type: Oracle Analytics Cloud is subscription-based. Licensing metrics typically include per-user subscriptions (e.g., Viewer vs. Creator tiers) or per-OCPU (Oracle Compute Unit) usage. Cloud deployments may also utilize a Bring Your Own License (BYOL) model for existing Oracle licenses.
• Deployment Model: Primarily a cloud-based service (PaaS). It can be deployed in a hybrid model alongside Oracle Analytics Server (OAS) for on-premises components. OAC instances can have public or private endpoints.

Technical Requirements

• RAM: Not directly specified for the cloud service itself, as Oracle manages the underlying infrastructure. Performance scales with OCPU allocation.
• Processor: Not directly specified for the cloud service. Processing capacity is managed and scaled using Oracle Compute Units (OCPUs), ranging from 2 to 52 OCPUs depending on workload.
• Storage: Not directly specified for the cloud service. Data storage is handled within the Oracle Cloud Infrastructure (OCI) environment, including object storage.
• Display: Standard display requirements for web-based access and client tools.
• Ports: Connectivity to OAC typically occurs over standard HTTPS ports. Specific ports may be required for connecting to various data sources, especially on-premises ones, often facilitated by Remote Data Gateway.
• Operating System: For client-side components like Oracle Data Gateway, supported OS include various versions of Oracle Linux, Red Hat Enterprise Linux, SLES, and Microsoft Windows.

Analysis of Technical Requirements: Oracle Analytics Cloud is a fully managed cloud service, meaning the technical infrastructure requirements (RAM, processor, storage) are largely abstracted from the end-user. Oracle handles the provisioning, scaling, and maintenance of these resources. Users manage performance by adjusting the number of OCPUs allocated to their OAC instance, which can be scaled up or down without downtime. Client-side requirements are minimal, primarily concerning the operating system for data gateway installations, ensuring broad compatibility for connecting to on-premises data sources. This cloud-native approach simplifies deployment and reduces the operational burden on enterprises.

Support & Compatibility

• Latest Version: Oracle Analytics Cloud receives continuous updates, with recent significant updates in January and May 2025.
• OS Support: Client-side components like Oracle Data Gateway support Oracle Linux, Red Hat Enterprise Linux, SLES, and Microsoft Windows.
• End of Support Date: As a cloud service, support is continuous and included with the subscription.
• Localization: Oracle Analytics Cloud supports various languages for its user interface and content.
• Available Drivers: OAC offers a wide range of out-of-the-box native connectors for various data sources, including Oracle databases (ADW, ATP, EPM Cloud, Essbase, NetSuite, Fusion Cloud Applications), and non-Oracle sources like Amazon Redshift, Apache Hive, Databricks, Google Analytics, Google BigQuery, Microsoft Azure SQL Database, MongoDB, PostgreSQL, Salesforce, Snowflake, and SQL Server. It also supports Java Database Connectivity (JDBC) for other sources.

Analysis of Overall Support & Compatibility Status: Oracle Analytics Cloud demonstrates strong support and compatibility, particularly within the Oracle ecosystem. Its continuous update model ensures users always have access to the latest features and security patches. Broad operating system support for client tools facilitates integration with diverse enterprise environments. The extensive list of native data connectors, encompassing both Oracle and third-party cloud and on-premises sources, highlights its versatility in data integration. The ability to connect via JDBC further extends its reach to a wide array of legacy and specialized systems. This comprehensive connectivity and continuous support make OAC a highly compatible and adaptable analytics platform.

Security Status

• Security Features: OAC offers robust governance features, including data access management, security policies, and user roles. It provides data encryption, access controls, and integration with existing security infrastructure. Data-level security, object permissions, and query limits are enforced by the Oracle Analytics query engine.
• Known Vulnerabilities: Oracle regularly releases security updates and patches for its cloud services. Specific public vulnerabilities for OAC are typically addressed promptly through these updates.
• Blacklist Status: Not applicable; OAC is a legitimate cloud service.
• Certifications: Oracle Cloud Infrastructure (OCI), on which OAC runs, adheres to numerous global and industry-specific compliance certifications (ee.g., ISO, SOC, HIPAA, FedRAMP).
• Encryption Support: Data within Oracle Analytics Cloud is encrypted by default using Oracle-managed keys. Customers can optionally use customer-managed encryption keys via Oracle Cloud Infrastructure Vault services for data at rest, including file-based datasets, cached data, and data source credentials. Data in transit is also encrypted.
• Authentication Methods: OAC integrates with Oracle Identity Cloud Service (IDCS) for cloud authentication. It supports Single Sign-On (SSO) and can federate with other identity providers like Microsoft Active Directory. OAuth 2.0 authentication, including bearer tokens and device authorization grant flow, is supported for accessing OAC APIs and embedded content.
• General Recommendations: Implement row-level security in the database and object permissions and query limits in the semantic model. Utilize customer-managed encryption keys for enhanced control over sensitive data. Configure robust identity management with SSO and MFA where possible.

Analysis on Overall Security Rating: Oracle Analytics Cloud provides a strong security posture, leveraging the comprehensive security capabilities of Oracle Cloud Infrastructure. Default encryption for data at rest and in transit, coupled with the option for customer-managed keys, offers significant data protection. Robust access controls, including role-based security, object permissions, and row-level security, ensure granular control over data access. Integration with Oracle Identity Cloud Service and support for various authentication methods, including OAuth 2.0 and SSO, provide flexible and secure user access management. Oracle's commitment to compliance certifications further solidifies its security rating, making OAC a secure platform for enterprise analytics.

Performance & Benchmarks

• Benchmark Scores: Specific public benchmark scores for OAC are not readily available, as performance is highly dependent on configuration and workload.
• Real-World Performance Metrics: OAC is built on a high-performance platform designed for scalability. It offers dynamic scaling of OCPUs to adjust to varying workloads, ensuring consistent performance during peak demand. Users can scale up or down OCPUs to improve performance or save costs.
• Power Consumption: As a cloud service, power consumption is managed by Oracle's data centers. Oracle Cloud Infrastructure focuses on energy efficiency and sustainability.
• Carbon Footprint: Oracle is committed to sustainability in its cloud operations.
• Comparison with Similar Assets: OAC is positioned as an AI-powered, self-service analytics platform that combines data visualization, self-service analytics, and machine learning capabilities. Users praise its seamless integration with Oracle databases and applications, built-in AI/ML features, and natural language query capabilities. It is often compared to other leading BI tools like Tableau and Power BI.

Analysis of Overall Performance Status: Oracle Analytics Cloud is designed for high performance and scalability, crucial for enterprise analytics. Its cloud-native architecture allows for dynamic scaling of resources (OCPUs) to match demand, minimizing downtime and optimizing cost. While specific public benchmarks are scarce, user feedback and its integration with Oracle's high-performance cloud infrastructure suggest robust real-world performance. The platform's ability to handle large datasets and complex queries, combined with AI-driven insights, contributes to efficient data analysis. Its focus on seamless integration within the Oracle ecosystem further enhances performance for organizations already using Oracle products.

User Reviews & Feedback

• Strengths: Users frequently highlight OAC's seamless integration with Oracle databases and applications. The built-in AI and machine learning features, including automated insights and natural language query ("Ask") functions, are highly valued for making data exploration intuitive. Its powerful data visualization capabilities, user-friendly interface, and robust analytics for better decision-making are also praised. OAC is seen as an all-in-one platform combining visualization, self-service analytics, and ML with Oracle's cloud infrastructure.
• Weaknesses: Some users note challenges and higher costs when connecting to data from non-Oracle sources like Azure.
• Recommended Use Cases: OAC is recommended for organizations seeking to consolidate scattered data into clear, visual insights, saving time on reporting, supporting better decision-making, and identifying trends quickly. It is used for supply chain and inventory management, and for leveraging predictive data models and machine learning for deep insights and rapid data-driven decisions. It is also a viable migration path for existing Oracle Business Intelligence (OBI) users.

Summary

Oracle Analytics Cloud (OAC) is a comprehensive, AI-powered, self-service analytics platform designed for enterprise environments. It offers a robust suite of capabilities including data preparation, visualization, enterprise reporting, and augmented analytics, all delivered as a managed cloud service. OAC operates on a continuous update cycle, ensuring users benefit from the latest features and security enhancements, with recent updates in January and May 2025 introducing significant advancements in AI and connectivity.

A key strength of OAC lies in its cloud-native architecture, which abstracts underlying technical complexities. Performance scales dynamically through Oracle Compute Units (OCPUs), allowing organizations to adjust resources based on workload without downtime. This model significantly reduces the operational burden associated with managing analytics infrastructure. Compatibility is extensive, particularly within the Oracle ecosystem, with numerous native connectors for both Oracle and third-party data sources, and broader connectivity via JDBC.

Security is a paramount feature, leveraging Oracle Cloud Infrastructure's robust framework. OAC provides default and customer-managed encryption for data at rest and in transit, granular access controls (row-level security, object permissions), and strong authentication methods including SSO and OAuth 2.0 integration with Oracle Identity Cloud Service. This comprehensive approach ensures data privacy and compliance.

User feedback consistently highlights OAC's seamless integration with Oracle databases and applications, its intuitive AI and machine learning capabilities (such as natural language query and automated insights), and its powerful data visualization tools. While some users note potential challenges or costs with non-Oracle data source integration, the platform is widely recommended for consolidating data, enhancing decision-making, and leveraging advanced analytics for predictive insights across various business functions like supply chain management.

In conclusion, Oracle Analytics Cloud stands out as a highly scalable, secure, and feature-rich analytics platform, particularly well-suited for organizations deeply integrated with the Oracle ecosystem or those seeking a powerful, managed cloud solution for their business intelligence needs. Its continuous evolution and strong focus on AI and user experience position it as a leading choice for modern enterprise analytics.

Information provided is based on publicly available data and may vary depending on specific device configurations. For up-to-date information, please consult official manufacturer resources.