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 most valuable feature of Databricks is the notebook, data factory, and ease of use."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"Ability to work collaboratively without having to worry about the infrastructure."
"The time travel feature is the solution's most valuable aspect."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"It's great technology."
"The main features of the solution are efficiency."
"The technical support is excellent, and they respond quickly."
"It has the best feature for data augmentation."
"The features that I find to be the most valuable are the BAS (Business Analytics), the Narrate feature, and the auto-visualization."
"A valuable feature is the speed of the solution."
"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."
"The AI/ML enablement is useful, as many reporting tools do not offer machine learning models as of now, without writing customized code."
"The solution is user-friendly."
"Analytics Cloud allows you to merge various data types and structure data from multiple sources."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"A lot of people are required to manage this solution."
"We'd like a more visual dashboard for analysis It needs better UI."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"It should have more compatible and more advanced visualization and machine learning libraries."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The solution could be more flexible."
"It's not a failure of the product; it's just an architectural choice. It has to do with data modeling. I'm comparing this to another product, which is Oracle's developer client and probably called Oracle BI Developer Client Tool. The data modeler, which is cloud-based, and Oracle BI Developer Client Tool, which is local or on-premises-based, both can do the same thing in data modeling. However, the cloud tool does not have as many features as the Oracle BI Developer Client Tool, which is closest to the OBIEE Administration Tool with full feature data modeling, metadata development, and so forth. In a complex environment or implementation, that is the capability that you need."
"As with most BI tools, the visualizations can be made much nicer. Currently, it has standard visualizations. They've been adding new visualizations, but we see animated visualizations from other vendors. It would be nice to have similar visualizations, such as the swarming visualizations, which are fairly new and very popular at the moment. I haven't seen that with Oracle. That would be nice."
"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."
"The implementation of generative AI and machine learning should improve"
"One area of improvement is associated with more connectors needing to be added such as Microsoft OneDrive, Teradata and a few others. I think the list is limited to the top ones now."
"The product should be improved in terms of connectors; right now the top twenty connectors are available, but OneDrive and Teradata are missing."
"It should simplify data connectivity and modeling, making data extraction more streamlined and adaptable for diverse use cases."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Oracle Analytics Cloud is ranked 8th in BI (Business Intelligence) Tools with 25 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, Dremio and Confluent, whereas Oracle Analytics Cloud is most compared with Oracle OBIEE, Microsoft Power BI, Tableau, Oracle Business Intelligence Cloud Service and SAP Analytics Cloud. See our Databricks vs. Oracle Analytics Cloud report.
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