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Top 10 Dataiku Alternatives

Vendor: Dataiku
4.0 out of 5
1,124 followers
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Top Dataiku Competitors

Discover the top alternatives and competitors to Dataiku based on the interviews we conducted with its users. The top alternative solutions include Databricks, Microsoft Azure Machine Learning Studio, and KNIME. The alternatives are sorted based on how often peers compare the solutions.

Dataiku Alternatives Report

Learn what solutions real users are comparing with Dataiku, and compare use cases, valuable features, and pricing.
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Databricks
4.1 out of 5
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Databricks
4.1 out of 5
Organizations use Databricks for analytics queries, data processing, ETL, machine learning, AI, and data engineering on multi-node clusters. They appreciate its ease of use and scalability with features like a collaborative notebook interface, support for SQL, Python, and R, and excellent data processing. Databricks needs better visualization, integration, and support for improvement.
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Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.
I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.
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Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.
I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.
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Microsoft Azure Machine Learning Studio
3.8 out of 5
Microsoft Azure Machine Learning Studio offers diverse features like AutoML, appealing to non-programmers. In comparison, Dataiku excels with visual data preparation and supports multiple coding languages, ideal for technical users. Azure's flexible deployment contrasts with Dataiku's emphasis on on-premises solutions.
Download Dataiku vs. Microsoft Azure Machine Learning Studio Report
Microsoft Azure Machine Learning Studio offers a more competitive setup cost compared to Dataiku, which requires a higher initial investment, highlighting a significant pricing difference for users evaluating initial platform costs.
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Microsoft Azure Machine Learning Studio offers a more competitive setup cost compared to Dataiku, which requires a higher initial investment, highlighting a significant pricing difference for users evaluating initial platform costs.
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KNIME
4.1 out of 5
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KNIME
4.1 out of 5
KNIME integrates with R and Python, enabling visual workflows and offering free open-source desktop access. In comparison, Dataiku combines workflows and machine learning, providing predefined recipes for data handling. KNIME excels with community support, while Dataiku's features justify its higher pricing.
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KNIME offers a competitive setup cost, making it a budget-friendly choice, while Dataiku may require a higher initial investment, highlighting a key difference in the expenses for potential users.
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KNIME offers a competitive setup cost, making it a budget-friendly choice, while Dataiku may require a higher initial investment, highlighting a key difference in the expenses for potential users.
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Alteryx
4.2 out of 5
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Alteryx
4.2 out of 5
Alteryx offers intuitive, code-free data preparation with strong integration, ideal for users needing efficient large dataset handling. In comparison, Dataiku excels in machine learning and diverse modeling. With different deployment options, Alteryx addresses various needs, while Dataiku's machine learning focus caters to scientific workflows.
Download Alteryx vs. Dataiku Report
Alteryx setup cost is notably higher, focusing on premium offerings, whereas Dataiku presents a more budget-friendly setup, appealing to cost-conscious users.
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Alteryx setup cost is notably higher, focusing on premium offerings, whereas Dataiku presents a more budget-friendly setup, appealing to cost-conscious users.
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Amazon SageMaker
3.9 out of 5
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Amazon SageMaker
3.9 out of 5
Dataiku's user-friendly interface encourages team collaboration and simplifies workflows. In comparison, Amazon SageMaker offers extensive features, deep AWS integration, and scalability. Dataiku's transparent pricing appeals to smaller teams, while SageMaker provides robust ROI for those utilizing its comprehensive capabilities.
Download Amazon SageMaker vs. Dataiku Report
Dataiku is often praised for its straightforward setup process, while Amazon SageMaker's initial cost setup can be complex and varied.
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Dataiku is often praised for its straightforward setup process, while Amazon SageMaker's initial cost setup can be complex and varied.
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RapidMiner
4.3 out of 5
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RapidMiner
4.3 out of 5
RapidMiner is favored for its user-friendly drag-and-drop design and competitive pricing, ideal for budget-conscious businesses. In comparison, Dataiku's comprehensive scalability, data integration capabilities, and flexible deployment options make it a strong choice for enterprises needing extensive analytics and governance.
Download Dataiku vs. RapidMiner Report
RapidMiner offers a more cost-effective initial setup compared to Dataiku, while Dataiku provides a more comprehensive feature set requiring a significant investment.
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RapidMiner offers a more cost-effective initial setup compared to Dataiku, while Dataiku provides a more comprehensive feature set requiring a significant investment.
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IBM SPSS Statistics
4.0 out of 5
IBM SPSS Statistics offers comprehensive statistical capabilities ideal for industries requiring advanced analytics, despite higher pricing. In comparison, Dataiku excels in machine learning and data preparation, making it a preferred choice for businesses seeking operational efficiency and streamlined workflows.
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IBM SPSS Statistics offers lower setup costs, while Dataiku's setup costs are comparatively higher, but the latter may provide additional advanced features.
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IBM SPSS Statistics offers lower setup costs, while Dataiku's setup costs are comparatively higher, but the latter may provide additional advanced features.
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Dremio
4.3 out of 5
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Dremio
4.3 out of 5
Dataiku offers a collaborative data processing and machine learning environment, emphasizing ease of use and support. In comparison, Dremio excels in SQL analytics, prioritizing query performance and customization. Both deliver unique advantages for distinctive organizational needs, supporting different buyer priorities.
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Dataiku's setup cost is higher compared to Dremio, which offers a more affordable initial investment option.
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Dataiku's setup cost is higher compared to Dremio, which offers a more affordable initial investment option.
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IBM Watson Studio
4.1 out of 5
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IBM Watson Studio
4.1 out of 5
IBM Watson Studio offers strong data integration and cloud scalability. In comparison, Dataiku excels in collaboration and machine learning for intricate analyses. Tech buyers might choose Watson Studio for flexible pricing or Dataiku for its comprehensive features enhancing productivity and efficiency.
Download Dataiku vs. IBM Watson Studio Report
IBM Watson Studio offers variable setup costs depending on specific use cases, while Dataiku provides a more uniform structure, highlighting distinct approaches to deployment and initial investment.
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IBM Watson Studio offers variable setup costs depending on specific use cases, while Dataiku provides a more uniform structure, highlighting distinct approaches to deployment and initial investment.
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IBM SPSS Modeler
4.0 out of 5
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IBM SPSS Modeler
4.0 out of 5
IBM SPSS Modeler is appreciated for its robust statistical analysis capabilities, catering to data-driven organizations. In comparison, Dataiku excels in integration and collaboration, appealing to team-oriented environments. Tech buyers might choose IBM for predictability and Dataiku for comprehensive features and scalability.
Download Dataiku vs. IBM SPSS Modeler Report
IBM SPSS Modeler has a higher setup cost compared to Dataiku, making Dataiku a more cost-effective option for initial implementation.
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IBM SPSS Modeler has a higher setup cost compared to Dataiku, making Dataiku a more cost-effective option for initial implementation.
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Anaconda
4.1 out of 5
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Anaconda
4.1 out of 5
Anaconda, favored for its open-source approach, excels in package management and tools for Python and R. In comparison, Dataiku is preferred for comprehensive integration and machine learning capabilities. Anaconda suits budget-conscious users, while Dataiku targets enterprises due to its extensive features and support.
Download Anaconda vs. Dataiku Report
Anaconda's setup cost is often more economical than Dataiku, making it a budget-friendly choice for many organizations. In contrast, Dataiku offers extensive features and support that justify its higher setup investment.
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Anaconda's setup cost is often more economical than Dataiku, making it a budget-friendly choice for many organizations. In contrast, Dataiku offers extensive features and support that justify its higher setup investment.
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Domino Data Science Platform
3.8 out of 5
Dataiku is favored for its competitive pricing and support, attracting budget-conscious buyers. In comparison, Domino Data Science Platform offers superior features and advanced capabilities, appealing to those investing in comprehensive model management and experiment tracking, despite a steeper learning curve and higher upfront costs.
Download Dataiku vs. Domino Data Science Platform Report
Dataiku's setup cost is more budget-friendly, emphasizing a cost-effective approach, while Domino Data Science Platform presents a higher initial expense, suggesting a focus on enterprises willing to invest more heavily from the start.
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Dataiku's setup cost is more budget-friendly, emphasizing a cost-effective approach, while Domino Data Science Platform presents a higher initial expense, suggesting a focus on enterprises willing to invest more heavily from the start.
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Starburst Enterprise
4.3 out of 5
Dataiku offers superior integration and team collaboration features for streamlined analytics workflows. In comparison, Starburst Enterprise excels in scalability and supports complex analytics with robust security. Tech buyers might choose Dataiku for ease of deployment or Starburst Enterprise for high performance in large-scale operations.
Download Dataiku vs. Starburst Enterprise Report
Dataiku reviews highlight its lower setup costs, whereas Starburst Enterprise incurs higher initial fees.
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Dataiku reviews highlight its lower setup costs, whereas Starburst Enterprise incurs higher initial fees.
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H2O.ai
3.8 out of 5
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H2O.ai
3.8 out of 5
Dataiku attracts non-technical users with its user-friendly interface and strong integration capabilities. In comparison, H2O.ai appeals to data scientists with its sophisticated algorithms and customizable features. Dataiku's higher initial cost can lead to quick ROI, while H2O.ai offers scalable pricing.
Download Dataiku vs. H2O.ai Report
Dataiku charges a higher setup cost compared to H2O.ai, offering an extensive range of features, while H2O.ai provides a more cost-effective setup with basic functionalities ideal for budget-conscious users.
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Dataiku charges a higher setup cost compared to H2O.ai, offering an extensive range of features, while H2O.ai provides a more cost-effective setup with basic functionalities ideal for budget-conscious users.
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Cloudera Data Science Workbench
3.5 out of 5
Dataiku excels in user experience and flexibility, appealing to teams seeking collaboration and efficiency. In comparison, Cloudera Data Science Workbench is favored for performance and integration, catering to organizations requiring robust data processing and advanced analytics within Cloudera's ecosystem.
Download Cloudera Data Science Workbench vs. Dataiku Report
Dataiku offers lower setup costs compared to Cloudera Data Science Workbench, which may appeal to budget-conscious businesses.
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Dataiku offers lower setup costs compared to Cloudera Data Science Workbench, which may appeal to budget-conscious businesses.
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SAS Enterprise Miner
3.8 out of 5
SAS Enterprise Miner provides deep analytical capabilities ideal for intricate data mining. In comparison, Dataiku offers a user-friendly collaboration environment through an integrated platform. SAS Enterprise Miner suits data-focused organizations, whereas Dataiku appeals to those prioritizing quick implementation and ease of use.
Download Dataiku vs. SAS Enterprise Miner Report
SAS Enterprise Miner has higher setup costs compared to Dataiku, which offers a more budget-friendly initial investment while maintaining robust data analytics features.
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SAS Enterprise Miner has higher setup costs compared to Dataiku, which offers a more budget-friendly initial investment while maintaining robust data analytics features.
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Starburst Galaxy
1 out of 5
Starburst Galaxy enhances data analytics capabilities by offering powerful data processing and querying features. Users appreciate its scalability and flexibility. However, there's room for improvement in integration with other platforms and documentation clarity.
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MathWorks Matlab
4.3 out of 5
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MathWorks Matlab
4.3 out of 5
Dataiku offers a collaborative environment and ease of use, making it ideal for quick deployment and user accessibility. In comparison, MathWorks Matlab, with its extensive mathematical functions and advanced visualizations, suits enterprises seeking sophisticated analytical capabilities and robust computational tools for complex data analysis.
Download Dataiku vs. MathWorks Matlab Report
Dataiku has a straightforward setup cost that appeals to businesses focused on budget-friendly deployment, while MathWorks Matlab involves a more complex setup process, potentially impacting the initial investment and planning required for implementation.
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Dataiku has a straightforward setup cost that appeals to businesses focused on budget-friendly deployment, while MathWorks Matlab involves a more complex setup process, potentially impacting the initial investment and planning required for implementation.
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TIBCO Data Science
3.8 out of 5
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TIBCO Data Science
3.8 out of 5
TIBCO Data Science is favored for its pricing and robust integration capabilities. In comparison, Dataiku excels with intuitive collaboration and comprehensive machine learning features. TIBCO's smooth deployment attracts buyers, while Dataiku's scalability and ROI appeal to businesses focused on long-term growth.
Download Dataiku vs. TIBCO Data Science Report
TIBCO Data Science has a higher setup cost compared to Dataiku, highlighting a noticeable difference in initial financial investment between the two solutions.
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TIBCO Data Science has a higher setup cost compared to Dataiku, highlighting a noticeable difference in initial financial investment between the two solutions.
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WPS Analytics
1 out of 5
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WPS Analytics
1 out of 5

WPS is used in production on a huge range of systems at sites around the world. Thousands of analysts are using WPS in their daily data processing and analysis tasks, and thousands more rely on the heavy-lifting ability of WPS overnight and scheduled processing to deliver the information they require. Customers are able to choose to run WPS software on IBM z/OS Mainframes, servers and workstations running UNIX, Linux, Solaris, AIX, macOS and the full range of Microsoft Windows operating systems to fit in with existing or planned infrastructure.

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