Dataiku vs Dremio comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.2
Number of Reviews
7
Ranking in other categories
No ranking in other categories
Dremio
Ranking in Data Science Platforms
10th
Average Rating
8.6
Number of Reviews
6
Ranking in other categories
Cloud Data Warehouse (11th)
 

Mindshare comparison

As of June 2024, in the Data Science Platforms category, the mindshare of Dataiku is 9.9%, up from 6.7% compared to the previous year. The mindshare of Dremio is 5.8%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
Unique Categories:
No other categories found
Cloud Data Warehouse
2.8%
 

Featured Reviews

RK
May 17, 2024
Gives different aspects of modeling approaches and good for multiple teams' collaboration
I used DataRobot. Dataiku has a different kind of structure to it. It's not financially heavy like DataRobot, which caters more to financial companies, like banks. Dataiku doesn't have that yet. I think they are also working on that area. But yeah, there are some key differences between the two products. DataRobot has an additional feature with financial firms that it creates all these financial metrics when you run a time series analysis. Those things I have not seen in Dataiku. If any financial company is choosing between DataRobot and Dataiku, they will definitely go for DataRobot because it creates all these financial metrics. It creates deltas, time series, time difference fields, and things like that. So, that is an added feature that DataRobot has.
AM
Jan 16, 2024
A highly stable solution that works like a data warehouse on top of data lakes
Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported. The use case I am working on requires building trees and hierarchical structures. Most of the time, it requires complex nested data structures to be made simpler for end users. It would be good if Dremio could provide a way to create trees just like Oracle does using commands like CONNECT BY and NO CYCLE. You can use a few languages to simplify complicated JSON and XML. It would be very helpful if Dremio could provide a solution to simplify building trees and building meaningful data from complex data.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"Data Science Studio's data science model is very useful."
"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."
"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 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."
 

Cons

"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I think it would help if Data Science Studio added some more features and improved the data model."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"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."
"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."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"It shows errors sometimes."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"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."
 

Pricing and Cost Advice

"Pricing is pretty steep. Dataiku is also not that cheap."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
"Dremio is less costly competitively to Snowflake or any other tool."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Manufacturing Company
8%
Computer Software Company
7%
Financial Services Firm
31%
Computer Software Company
11%
Manufacturing Company
8%
Retailer
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend towards a tool.
What needs improvement with Dataiku Data Science Studio?
The no-code/low-code aspect, where DataRobot doesn't need much coding at all. Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot m...
What is your primary use case for Dataiku Data Science Studio?
My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataiku as a Jupyter Notebook. We use it a lot for marketing and analytics. The market...
What do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
Every tool has a value based on its visualization, and the pricing is worth its value.
What needs improvement with Dremio?
Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I cannot use the recursive common table expression (CTE) in Dremio because the supp...
 

Comparisons

 

Also Known As

Dataiku DSS
No data available
 

Learn More

Video not available
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Dataiku vs. Dremio and other solutions. Updated: May 2024.
789,674 professionals have used our research since 2012.