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."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."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"We primarily use Dremio to create a data framework and a data queue."
"Dremio allows querying the files I have on my block storage or object storage."
"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."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"This solution is easy to use and especially good at data preparation and wrapping."
"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."
"This solution is easy to use and it can be used to create any kind of model."
"There are a lot of connectors available in KNIME."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"KNIME is easy to learn."
"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."
"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."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"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."
"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."
"I've had some problems integrating KNIME with other solutions."
"KNIME is not good at visualization."
"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."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
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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