We performed a comparison between Apache Superset and Oracle Analytics Cloud based on real PeerSpot user reviews.
Find out in this report how the two Data Visualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Apache Superset is the easy way to configure dashboards as reports or analyses and it's easy to use and intuitive. Users do not need a lot of training to use the solution."
"It is a good visual solution tool in an open-source category."
"The solution supports a rich set of charts and enables users to create their own dashboards."
"It's really an enterprise solution. It has a dashboard, like standard dashboarding functionality. It also has reporting capabilities for producing pixel-perfect reports, bursting large volumes of a document if you need to. It has interactive data discovery functionality, which you would use to explore your data, bring your own data, and merge it with maybe the data from an enterprise data warehouse to get new insights from the pre-existing data. It has machine learning embedded in the solution. If you're new to machine learning, it's a really good way to get into it, because it's all within this platform, and it's really easy to use."
"The specific capability I find important in Oracle Analytics Cloud is that it allows the basic user to easily drag and drop data. I also like that the solution allows the user to decide what to measure and what to see in the reports."
"Data preparation is fantastic and fast. We were able to use multiple data sources and prepare the data quickly."
"The technical support services are good."
"I've discovered that the new layout of this product makes Docker sharing, machine learning support, and data backups more efficient. Unlike the older method of linking physical, pre-logical, and presentation layers separately, the new interface simplifies this process. Additionally, the integration of databases and machine learning is seamless, with the new visualization approach being particularly beautiful and highly beneficial."
"It plays a crucial role in facilitating decision-making for various organizational stakeholders."
"The advanced calculations by the tool are highly effective"
"The AI/ML enablement is useful, as many reporting tools do not offer machine learning models as of now, without writing customized code."
"Automation in terms of APIs for creating roles, and giving privileges to the user can be improved."
"The platform's reporting feature needs enhancement."
"Dynamic dashboarding could improve to enable smooth navigation when transitioning from a higher to a lower view, allowing for easy accessibility."
"The product could benefit from increased flexibility compared to other vendors."
"The migration of older dash tools from the classic interface of Oracle BI prior to OAS launch to the newer Data Visualization and Oracle Analytics Cloud interfaces, including dashboards and metadata, is currently a cumbersome process. Improvements in this area would be highly beneficial. Additionally, the administration of the cloud, particularly the startup of services and linking of the WebLogic server and integrated components, takes longer than desired. In today's enterprise landscape, waiting forty minutes for the server to be operational is quite lengthy; ideally, this process should take a maximum of four minutes. It would be excellent to incorporate metadata management as an integral part of the Oracle Analytics Cloud. When dealing with integrated data from various sources, tracking data lineage and the entire data life cycle, from sources to report development and the mapping of reports to specific dashboards, should be seamlessly managed within the Oracle Analytics Cloud. This would eliminate the need for additional tools. Drawing a comparison, tools like Tableau have a feature enabling metadata management, making it easier to trace the complete data lineage of reports. Managing over seven hundred and thirty-six business dashboards, the metadata management capability within Tableau simplified the process of understanding how reports were developed, including details like associated tables, users, linked views, materialized views, data segmentations, ETL jobs, and the data warehouse stages. Enhancing metadata tracking within the Oracle Analytics Cloud layout would facilitate easy and practical management of the complete data life cycle, encompassing user accessibility and report permissions."
"The product should be improved in terms of connectors; right now the top twenty connectors are available, but OneDrive and Teradata are missing."
"The solution could be more flexible."
"The implementation of generative AI and machine learning should improve"
"When you implement the product on a small scale, it doesn't generate any ROI."
"It should simplify data connectivity and modeling, making data extraction more streamlined and adaptable for diverse use cases."
"When we have, for example, a table with low performance, we have several issues with drawing some graphics in the Oracle cloud."
Apache Superset is ranked 11th in Data Visualization with 3 reviews while Oracle Analytics Cloud is ranked 6th in Data Visualization with 25 reviews. Apache Superset is rated 8.0, while Oracle Analytics Cloud is rated 8.0. The top reviewer of Apache Superset writes "Has some great features and supports a rich set of charts". On the other hand, the top reviewer of Oracle Analytics Cloud writes "Reliable, capable of handling massive amounts of data, and good value for money". Apache Superset is most compared with Qlik Sense, Tableau, Splunk Enterprise Platform, Sisense and ThoughtSpot, whereas Oracle Analytics Cloud is most compared with Databricks, Oracle OBIEE, Tableau, Microsoft Power BI and Workday Prism Analytics. See our Apache Superset vs. Oracle Analytics Cloud report.
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