We performed a comparison between Databricks and KNIME 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."The most valuable feature of Databricks is the integration with Microsoft Azure."
"It's great technology."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"The initial setup phase of Databricks was good."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"We can deploy the solution in a cluster as well."
"I was able to apply basic algorithms through just dragging and dropping."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"I would rate the stability of KNIME a ten out of ten."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way."
"It has allowed us to easily implement advanced analytics into various processes."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The initial setup is difficult."
"There are no direct connectors — they are very limited."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"Databricks has a lack of debuggers, and it would be good to see more components."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"KNIME is not good at visualization."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"KNIME's documentation is not strong."
"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Databricks is rated 8.2, while KNIME 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 KNIME writes "A low-code platform that reduces data mining time by linking script". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Amazon SageMaker. See our Databricks vs. KNIME report.
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