We compared Databricks and Dataiku Data Science Studio based on our user's reviews in several parameters.
In summary, Databricks is praised for its seamless integration and advanced analytics capabilities, while also receiving positive feedback on customer service and pricing. Dataiku Data Science Studio, on the other hand, is appreciated for its intuitive interface and powerful machine learning tools, with users expressing satisfaction with customer support and pricing flexibility. Both platforms offer valuable solutions for data management and analytics, with room for improvement in areas such as data visualization and feature development.
Features: Databricks stands out for its seamless integration with data sources and platforms, collaborative features, advanced analytics, and machine learning capabilities. Dataiku's key strengths lie in its intuitive interface, powerful machine learning capabilities, and seamless integration with various data sources and tools. Users appreciate Dataiku's ease of navigation, efficient machine learning functionalities, and the ability to connect with preferred systems for enhanced workflow efficiency.
Pricing and ROI: Databricks has positive user feedback on pricing, setup cost, and licensing. The pricing is reasonable and competitive, and the setup cost is straightforward. The license terms are flexible. Dataiku Data Science Studio users find the pricing plans affordable and suitable, and the setup cost manageable. The licensing options allow for seamless integration., Databricks users appreciate its value in increasing efficiency, productivity, and data analysis capabilities. Dataiku Data Science Studio users report significant cost savings, improved decision making, increased revenue generation, and valuable investments. Integrations and collaboration contribute to a positive ROI.
Room for Improvement: Databricks needs improvements in data visualization, monitoring and debugging tools, integration with external data sources, documentation for beginners, and pricing flexibility. Dataiku Data Science Studio requires enhancements in various features to optimize its platform.
Deployment and customer support: The user reviews for Databricks show varying durations for deployment, setup, and implementation. Some users mention spending three months on deployment and an additional week on setup, while others mention just a week for both. On the other hand, the reviews for Dataiku Data Science Studio mention different durations for each phase, but suggest considering deployment and setup together if they are within a short timeframe., Databricks provides efficient, helpful, and prompt customer service with knowledgeable and responsive staff. Their support team is proactive in solving issues. Dataiku also offers satisfactory customer service, with prompt and effective staff who provide knowledgeable and friendly assistance.
The summary above is based on 48 interviews we conducted recently with Databricks and Dataiku Data Science Studio users. To access the review's full transcripts, download our report.
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"There are good features for turning off clusters."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"It can send out large data amounts."
"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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"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."
"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."
"Data Science Studio's data science model is very useful."
"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"There should be better integration with other platforms."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"The Databricks cluster can be improved."
"Costs can quickly add up if you don't plan for it."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"It's not easy to use, and they need a better UI."
"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."
"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."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"The ability to have charts right from the explorer would be an improvement."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"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."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Dataiku is ranked 11th in Data Science Platforms with 7 reviews. Databricks is rated 8.2, while Dataiku is rated 8.2. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Dataiku writes "Gives different aspects of modeling approaches and good for multiple teams' collaboration". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dremio, Microsoft Azure Machine Learning Studio and Azure Stream Analytics, whereas Dataiku is most compared with KNIME, Alteryx, RapidMiner, Microsoft Azure Machine Learning Studio and Amazon SageMaker. See our Databricks vs. Dataiku report.
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