We performed a comparison between Databricks and IBM Watson Studio 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."It's great technology."
"We have the ability to scale, collaborate and do machine learning."
"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 time travel feature is the solution's most valuable aspect."
"The solution offers a free community version."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"Databricks integrates well with other solutions."
"The most valuable feature is the ability to use SQL directly with Databricks."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"It has a lot of data connectors, which is extremely helpful."
"It is a very stable and reliable solution."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It is a stable, reliable product."
"Watson Studio is very stable."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"Stability-wise, it is a great tool."
"The Databricks cluster can be improved."
"I have seen better user interfaces, so that is something that can be improved."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"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."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The pricing of Databricks could be cheaper."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"It should have more compatible and more advanced visualization and machine learning libraries."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"The solution's interface is very slow at times."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The initial setup was complex."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"The decision making in their decision making feature is less good than other options."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews. Databricks is rated 8.2, while IBM Watson Studio is rated 8.2. 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 Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM Watson Studio is most compared with Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI, Amazon Comprehend and Anaconda. See our Databricks vs. IBM Watson Studio report.
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