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."Everyone uses Dremio in my company; some use it only for the analytics function."
"Dremio allows querying the files I have on my block storage or object storage."
"We primarily use Dremio to create a data framework and a data queue."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"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."
"This open-source product can compete with category leaders in ELT software."
"Overall KNIME serves its purpose and does a good job."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"This solution is easy to use and especially good at data preparation and wrapping."
"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."
"It has allowed us to easily implement advanced analytics into various processes."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"There are a lot of connectors available in KNIME."
"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."
"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."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"It shows errors sometimes."
"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."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"KNIME could improve when it comes to large data markets."
"The predefined workflows could use a bit of improvement."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"The pricing needs improvement."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"There should be better documentation and the steps should be easier."
"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."
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.
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