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."Ability to work collaboratively without having to worry about the infrastructure."
"The simplicity of development is the most valuable feature."
"It can send out large data amounts."
"It's very simple to use Databricks Apache Spark."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"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."
"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."
"There are good features for turning off clusters."
"All the different platforms are well integrated."
"Planning Analytics' best features include automatic updates and slicing."
"The product's stability is good."
"IBM Planning Analytics is easy to use and deploy. It is quick to develop. The calculation machine is also very fast."
"The tool is flexible."
"The most valuable feature is that it is able to slice and dice the data."
"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 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."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"Databricks can improve by making the documentation better."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The initial setup is difficult."
"The local authentication part is difficult to manage in the product, making it an area where improvements are required."
"Extracting data is a little slow."
"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."
"Adding predefined templates could be beneficial."
"Planning Analytics could be improved by adding automation features."
"It is a bit expensive, but it does the job."
"It would have been better if the solution was not just a tool kit."
"The tool should include features for prediction. It can also improve the scalability."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM Planning Analytics is ranked 5th in Business Performance Management with 22 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.