We performed a comparison between Databricks and IBM Planning Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The initial setup phase of Databricks was good."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"The ease of use and its accessibility are valuable."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"Databricks integrates well with other solutions."
"The simplicity of development is the most valuable feature."
"It's easy to increase performance as required."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"The flexibility of IBM Planning Analytics is a great feature of this solution. The design flexibility with data rules and defining calculations The ability to combine online and offline calculations are a benefit. Additionally, the forecasting features and predictive analytics is very good."
"The tool is flexible."
"The most valuable feature is that it is able to slice and dice the data."
"All the different platforms are well integrated."
"Navigating through the data to make analysis is really quick."
"It's a very stable, robust product."
"A lot of the platform is in-memory, so Planning Analytics can run calculations quite fast. It also offers several user interfaces. And in the newest version of Planning Analytics, there is a new one called the Planning Analytics Workspace. Maybe it could be useful for the business side."
"The product's stability is good."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"The integration of data could be a bit better."
"Doesn't provide a lot of credits or trial options."
"Databricks can improve by making the documentation better."
"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."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"The new frontend Planning Analytics Workspace is not very good, it could be improved. I like the Planning Analytics functionality but it would be helpful if it could be more customizable. You can create a prediction and receive information but you cannot do feature engineering regarding the predictive models. If this was added it would be helpful."
"The dashboard is very poor and needs a lot of improvement."
"It's wonky, and not super user-friendly with Excel."
"Planning Analytics could be improved by adding automation features."
"The local authentication part is difficult to manage in the product, making it an area where improvements are required."
"It is a bit expensive, but it does the job."
"Extracting data is a little slow."
"The tool's transport layer could be improved when promoting development between environments."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM Planning Analytics is ranked 6th in Business Performance Management with 21 reviews. Databricks is rated 8.2, while IBM Planning Analytics is rated 8.6. 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 IBM Planning Analytics writes "Can easily create dashboards and helps businesses improve forecasting accuracy". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM Planning Analytics is most compared with SAP Analytics Cloud, Microsoft Power BI, Anaplan, Jedox and Oracle HFM.
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.