We performed a comparison between Dremio 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."We primarily use Dremio to create a data framework and a data queue."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio allows querying the files I have on my block storage or object storage."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"It's a huge tool with machine learning features as well."
"There are a lot of connectors available in KNIME."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"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."
"This open-source product can compete with category leaders in ELT software."
"The solution allows for sharing model designs and model operations with other data analysts."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"It shows errors sometimes."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"KNIME is not good at visualization."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"The data visualization part is the area most in need of improvement."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"The predefined workflows could use a bit of improvement."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"The documentation needs a proper rework. "
Dremio is ranked 9th in Data Science Platforms with 6 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Dremio is rated 8.6, while KNIME is rated 8.2. The top reviewer of Dremio writes "It enables you to manage changes more effectively than any other platform". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Microsoft Azure Synapse Analytics, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Weka. See our Dremio vs. KNIME report.
See our list of best Data Science Platforms vendors.
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.