We performed a comparison between Databricks and Oracle Analytics Cloud based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"The setup was straightforward."
"The processing capacity is tremendous in the database."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"It's great technology."
"The technical support is excellent, and they respond quickly."
"Analytics Cloud allows you to merge various data types and structure data from multiple sources."
"The solution is user-friendly."
"The solution can scale."
"It has the best feature for data augmentation."
"Oracle Analytics Cloud's most valuable feature is its visualization."
"Mobility is the most valuable feature for us. All employees can access it from anywhere. It is a big advantage for us."
"It plays a crucial role in facilitating decision-making for various organizational stakeholders."
"In the next release, I would like to see more optimization features."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"The pricing of Databricks could be cheaper."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"It should have more compatible and more advanced visualization and machine learning libraries."
"Anyone who doesn't know SQL may find the product difficult to work with."
"Costs can quickly add up if you don't plan for it."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"The learning curve should be improved, and I'm uncertain if tutorials are readily available or easily accessible. We may have resorted to looking on YouTube for such information. Having easily understandable documents or guides for new users would be beneficial. AI integration would be an interesting feature to add in the next release."
"Sharing dataflows is not possible at this time, and the custom chart functionality is not available."
"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 scalability has room for improvement."
"When we have, for example, a table with low performance, we have several issues with drawing some graphics in the Oracle cloud."
"This solution could be more adaptable in its application."
"They could improve the ease of developing the dashboard and interacting with it."
"It is expensive."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Oracle Analytics Cloud is ranked 9th in BI (Business Intelligence) Tools with 24 reviews. Databricks is rated 8.2, while Oracle Analytics Cloud is rated 8.0. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". 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". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and SAS Visual Analytics, whereas Oracle Analytics Cloud is most compared with Oracle OBIEE, Tableau, Microsoft Power BI, Oracle Business Intelligence Cloud Service and SAP Analytics Cloud. See our Databricks vs. Oracle Analytics Cloud report.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.