We performed a comparison between Anaconda and Dataiku 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 advantageous feature is the logic building."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"The notebook feature is an improvement over RStudio."
"It helped us find find the optimal area for where our warehouse should be located."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"The solution is stable."
"The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors."
"The virtual environment is very good."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Data Science Studio's data science model is very useful."
"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."
"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."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The solution is quite stable."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The most valuable feature is the set of visual data preparation tools."
"It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database."
"It also takes up a lot of space."
"One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"When you install Anaconda for the first time, it's really difficult to update it."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"Anaconda can't handle heavy workloads."
"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."
"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."
"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."
"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."
"The ability to have charts right from the explorer would be an improvement."
"I think it would help if Data Science Studio added some more features and improved the data model."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
Anaconda is ranked 13th in Data Science Platforms with 17 reviews while Dataiku is ranked 7th in Data Science Platforms with 7 reviews. Anaconda is rated 8.0, while Dataiku is rated 8.2. The top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". On the other hand, the top reviewer of Dataiku writes "Gives different aspects of modeling approaches and good for multiple teams' collaboration". Anaconda is most compared with Databricks, Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI and MathWorks Matlab, whereas Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and Microsoft Azure Machine Learning Studio. See our Anaconda vs. Dataiku 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.
