KNIME Business Hub and Dataiku compete in the data science platform category. KNIME appears to have an advantage in pricing and open-source accessibility, while Dataiku stands out with a superior feature set and customer support.
Features: KNIME offers an extensive drag-and-drop interface, open-source flexibility, and integration with R, Python, and Java. Dataiku excels in machine learning capabilities, handling large datasets, and efficient workflow management.
Room for Improvement: KNIME needs enhancements in data visualization, documentation, and efficient handling of large datasets. Dataiku could improve its ease of learning and integration with external coding tools, as well as collaboration features.
Ease of Deployment and Customer Service: KNIME is often deployed on-premises or on public clouds, with a strong community for support. Dataiku provides both on-premises and cloud solutions, offering structured customer support, which is rated higher.
Pricing and ROI: KNIME is known for being cost-effective with a free desktop version and reasonably priced server version. Dataiku's higher costs can be a barrier for smaller businesses, though its advanced features may justify the investment for larger enterprises.
The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.
Dataiku partners with local industry experts who understand the business better and provide support.
The support team does not provide adequate assistance.
The customer service team is helpful and responsive, more or less on time.
While they cannot always provide immediate answers, they are generally efficient and simplify tasks, especially in the initial phase of learning KNIME.
In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.
I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.
It is not a very cost-effective solution, I must say, though it is good for developing purposes only.
Dataiku's pricing is very high, and commercial transparency is a challenge.
For graphics, the interface is a little confusing.
The machine learning and profileration aspects are fascinating and align with my academic background in statistics.
There are no extra expenses beyond the existing licensing cost.
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies.
The pricing for Dataiku is very high, which is its biggest downside.
Dataiku primarily enhances the speed at which our customers can develop or train their machine learning models because it is a drag-and-drop platform.
This feature is useful because it simplifies tasks and eliminates the need for a data scientist.
It offers most of the capabilities required for data science, MLOps, and LLMOps.
It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.
KNIME is more intuitive and easier to use, which is the principal advantage.
| Product | Market Share (%) |
|---|---|
| KNIME Business Hub | 11.9% |
| Dataiku | 11.7% |
| Other | 76.4% |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 16 |
| Large Enterprise | 29 |
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.
KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.
KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.
What are the most important features of KNIME Business Hub?KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.
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