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."Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"It is a cost-effective solution."
"Automation with Databricks is very easy when using the API."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"The main features of the solution are efficiency."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"Ability to work collaboratively without having to worry about the infrastructure."
"It has the best feature for data augmentation."
"The technical support services are good."
"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 product is easily customized."
"Data preparation is fantastic and fast. We were able to use multiple data sources and prepare the data quickly."
"Oracle Analytics Cloud's most valuable feature is its visualization."
"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 ability to quickly search for and access relevant data is crucial."
"The tool should improve its integration with other products."
"Databricks can improve by making the documentation better."
"The Databricks cluster can be improved."
"Databricks has a lack of debuggers, and it would be good to see more components."
"There is room for improvement in the documentation of processes and how it works."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"It would be great if Databricks could integrate all the cloud platforms."
"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."
"The scalability has room for improvement."
"The product should improve its user interface. It should be welcoming and modern. Developers should also find it easier to build data models. Oracle Analytics Cloud needs to have better visualizations and more options in the marketplace."
"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."
"It should simplify data connectivity and modeling, making data extraction more streamlined and adaptable for diverse use cases."
"The interfaces could be improved and some in-memory operations could be built in."
"Sharing dataflows is not possible at this time, and the custom chart functionality is not available."
"This solution could be more adaptable in its application."
"They could improve the ease of developing the dashboard and interacting with it."
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.
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