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 allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"It's great technology."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"The simplicity of development is the most valuable feature."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"The main features of the solution are efficiency."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"The technical support services are good."
"The features that I find to be the most valuable are the BAS (Business Analytics), the Narrate feature, and the auto-visualization."
"This is a stable and scalable solution."
"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 product is easily customized."
"The solution can scale."
"The solution is user-friendly."
"The best feature may be data flow, which is used to prepare and clean data."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"Databricks' technical support takes a while to respond and could be improved."
"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."
"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 solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"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."
"They could improve the ease of developing the dashboard and interacting with it."
"The product should be improved in terms of connectors; right now the top twenty connectors are available, but OneDrive and Teradata are missing."
"It is less scalable than Snowflake."
"When we have, for example, a table with low performance, we have several issues with drawing some graphics in the Oracle cloud."
"It should simplify data connectivity and modeling, making data extraction more streamlined and adaptable for diverse use cases."
"When you implement the product on a small scale, it doesn't generate any ROI."
"The solution could be more flexible."
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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