"The solution is very easy to use."
"It's great technology."
"It's easy to increase performance as required."
"The most valuable feature is the ability to use SQL directly with Databricks."
"Databricks helps crunch petabytes of data in a very short period of time."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The initial setup is pretty easy."
"Ability to work collaboratively without having to worry about the infrastructure."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It has a lot of data connectors, which is extremely helpful."
"IBM Watson Studio consistently automates across channels."
"There should be better integration with other platforms."
"The integration of data could be a bit better."
"It's not easy to use, and they need a better UI."
"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."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"There are no direct connectors — they are very limited."
"Pricing is one of the things that could be improved."
"Anyone who doesn't know SQL may find the product difficult to work with."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"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."
Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
Databricks is ranked 2nd in Data Science Platforms with 22 reviews while IBM Watson Studio is ranked 12th in Data Science Platforms with 3 reviews. Databricks is rated 7.8, while IBM Watson Studio is rated 8.6. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, the top reviewer of IBM Watson Studio writes "Machine learning that can be applicable for other data sets without having to carry out the process all over again". Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Azure Stream Analytics, Alteryx and Dataiku Data Science Studio, whereas IBM Watson Studio is most compared with Microsoft Azure Machine Learning Studio, IBM SPSS Modeler, Google Cloud Datalab, Amazon SageMaker and Anaconda. See our Databricks vs. IBM Watson Studio report.
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