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."Easy to use and requires minimal coding and customizations."
"The most valuable feature is the ability to use SQL directly with Databricks."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"Databricks' most valuable feature is the data transformation through PySpark."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"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."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The solution can scale."
"The best feature may be data flow, which is used to prepare and clean data."
"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."
"Mobility is the most valuable feature for us. All employees can access it from anywhere. It is a big advantage for us."
"Analytics Cloud allows you to merge various data types and structure data from multiple sources."
"It's valuable feature is that it is user-friendly and doesn't require much time for understanding. The solution is stable. The initial setup was straightforward."
"Data preparation is fantastic and fast. We were able to use multiple data sources and prepare the data quickly."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"The integration of data could be a bit better."
"There is room for improvement in visualization."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"In the next release, I would like to see more optimization features."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"Oracle Analytics Cloud is lacking in charts. They should add more charts to it."
"Its machine learning and visualization capabilities can be improved. There should be more visualization options."
"At this time, dataflows cannot be shared, but I think that this should be enhanced."
"Its FAW feature has limitations in terms of usage."
"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."
"This solution could be more adaptable in its application."
"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."
"It is less scalable than Snowflake."
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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