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Databricks Logo
28,492 views|18,008 comparisons
96% willing to recommend
Dataiku Logo
9,109 views|7,135 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary
Updated on Mar 6, 2024

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.

To learn more, read our detailed Databricks vs. Dataiku Report (Updated: May 2024).
771,740 professionals have used our research since 2012.
Q&A Highlights
Question: Which product would you choose for a data science team: Databricks vs Dataiku?
Answer: Databricks and Dataiku are excellent Data Science platforms but have different strengths and weaknesses. Below is a comparison of the two products based on several parameters: Cost It is reported that Databricks is a subscription-based service, and its cost varies based on the level of service you choose. They say the service also offers a free tier for development and testing purposes. Dataiku is also a subscription-based service, as reported, and the cost varies depending on the number of users and the features you need. The service also offers a free trial. Team Collaboration Databricks offers many features that help make team collaborations on Data Science projects easier, including notebooks, projects, and workspaces. Dataiku also offers several features for team collaboration, including shared projects, workspaces, and user permissions. Application Databricks may be a good choice for various Data Science applications, including Machine Learning, Data Engineering, and Data Visualization. Dataiku may also be worth considering for a wide range of Data Science applications, but they say it is particularly well-suited for Machine Learning. Data Security Databricks has several security features, including encryption, access control, and auditing. Dataiku also offers the above-mentioned security features. Databricks is a good choice for a wide range of data science applications and offers several features that make it easy for teams to collaborate. Databricks also offers a good level of data security. However, if your organization needs a Data Science platform more suitable for Machine Learning, Dataiku may be better.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"We can scale the product.""The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark.""Easy to use and requires minimal coding and customizations.""The integration with Python and the notebooks really helps.""The fast data loading process and data storage capabilities are great.""Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great.""The solution is easy to use and has a quick start-up time due to being on the cloud.""The most valuable feature of Databricks is the integration with Microsoft Azure."

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"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.""The solution is quite stable.""Cloud-based process run helps in not keeping the systems on while processes are running.""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.""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.""The most valuable feature is the set of visual data preparation tools."

More Dataiku Pros →

Cons
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity.""Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's.""Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with.""I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases.""I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one.""There would also be benefits if more options were available for workers, or the clusters of the two points.""The solution has some scalability and integration limitations when consolidating legacy systems.""The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."

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"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.""Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).""The ability to have charts right from the explorer would be an improvement.""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.""Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.""Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku.""I think it would help if Data Science Studio added some more features and improved the data model.""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."

More Dataiku Cons →

Pricing and Cost Advice
  • "Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
  • "I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
  • "Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
  • "We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
  • "The pricing depends on the usage itself."
  • "I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
  • "The price is okay. It's competitive."
  • "Databricks uses a price-per-use model, where you can use as much compute as you need."
  • More Databricks Pricing and Cost Advice →

  • "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."
  • "Pricing is pretty steep. Dataiku is also not that cheap."
  • More Dataiku Pricing and Cost Advice →

    report
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    771,740 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    Top Answer:We researched AWS SageMaker, but in the end, we chose Databricks Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… more »
    Top Answer:Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their… more »
    Top Answer:Databricks and Dataiku are excellent Data Science platforms but have different strengths and weaknesses. Below is a comparison of the two products based on several parameters Cost It is… more »
    Top Answer:Hi, I am the founder of Actable AI so my answer may be biased. In terms of performance, it's Actable AI. Why? Because we leverage the best and latest open source technologies out there (AutoGluon… more »
    Top Answer:Dataiku is my choice as it's not bulky and the learning path for people like me (noobs in ML and data science) is not steep at all, so after a couple of pieces of training I feel very confident. Also… more »
    Ranking
    1st
    Views
    28,492
    Comparisons
    18,008
    Reviews
    47
    Average Words per Review
    441
    Rating
    8.3
    11th
    Views
    9,109
    Comparisons
    7,135
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
    Also Known As
    Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
    Dataiku DSS
    Learn More
    Overview

    Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.

    Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.

    Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.

    Databricks Key Features

    Some of Databricks key features include:

    • Cloud-native: Works well on any prominent cloud provider.
    • Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
    • Self-governance: Built-in governance and security controls.
    • Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
    • Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
    • Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
    • Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
    • Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.

    Reviews from Real Users

    Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.

    PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”

    A business intelligence coordinator in construction notes, “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.”

    An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”

    Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

    Sample Customers
    Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
    BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
    Top Industries
    REVIEWERS
    Computer Software Company25%
    Financial Services Firm16%
    Retailer9%
    Manufacturing Company9%
    VISITORS READING REVIEWS
    Financial Services Firm15%
    Computer Software Company12%
    Manufacturing Company9%
    Healthcare Company6%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Educational Organization14%
    Manufacturing Company8%
    Computer Software Company8%
    Company Size
    REVIEWERS
    Small Business27%
    Midsize Enterprise14%
    Large Enterprise59%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise71%
    REVIEWERS
    Small Business57%
    Large Enterprise43%
    VISITORS READING REVIEWS
    Small Business12%
    Midsize Enterprise19%
    Large Enterprise68%
    Buyer's Guide
    Databricks vs. Dataiku
    May 2024
    Find out what your peers are saying about Databricks vs. Dataiku and other solutions. Updated: May 2024.
    771,740 professionals have used our research since 2012.

    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 "The model is very useful". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Microsoft Azure Machine Learning Studio, Dremio 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.

    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.