

Alteryx and Darwin are competitors in the advanced analytics and machine learning sector. Alteryx holds an edge with its comprehensive features and integration capabilities, positioning it as a versatile choice for data preparation and predictive tasks, while Darwin's strength lies in its automated model generation and enhancing data relationship accuracy.
Features: Alteryx offers data blending and predictive analytics, usable without coding. Its tools support geographic analysis and predictive modeling. Darwin excels with its automatic model generation, valuable for complex data relationships, and offers unique data quality assessment automation, saving time in model testing.
Room for Improvement: Alteryx needs better visualization capabilities directly within the tool, and improved In-DB functionalities to better align with external database tools. Darwin could enhance its user-friendly dashboard and refine its data quality assessment features to cater to users with less technical expertise.
Ease of Deployment and Customer Service: Alteryx primarily deploys on-premises, supported by a robust community, though its direct support could be more approachable. Darwin offers versatile deployment options including private and public cloud, maintaining smooth user experiences with minimal direct support requirements.
Pricing and ROI: Both Alteryx and Darwin have high costs, justified by significant returns. Alteryx's licensing is on the higher end but often provides considerable ROI through efficiency. Darwin's upfront cost is offset by reduced need for extensive data science resources, making it cost-effective.
Tasks that earlier took hours in Excel or SQL are now completed in minutes.
From a time-saving perspective, we saved 60 to 75 percent of the human workforce needed and eliminated other disparate ETL tools, ultimately saving us over 600,000 dollars.
Alteryx helps familiarize managers with artificial intelligence-driven possibilities.
Customer support from Alteryx has been amazing.
they do have a website for resolving doubts and accessing helpful resources, including various tools and filters.
I contacted customer support once or twice, and they were quick to respond.
Alteryx is scalable for most enterprise analytics and data preparation workloads.
Suggestions for improvements in Alteryx include areas for increasing efficiency, particularly in processing telemetry data, which involves dealing with large volumes of unstructured data.
Alteryx is scalable, and I would give it eight out of ten.
I didn't need to reach out to Alteryx for support because available documents usually provide enough information to resolve issues.
I have not encountered any lagging, crashing, or instability in the system during these three months of usage.
Alteryx is a reliable tool, but it is also very heavy, requiring good laptop configurations, a minimum of 8GB RAM, and a recent processor such as i10.
The tool could include more native connectors, such as for global ERPs, instead of requiring additional fees for these connections.
The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system.
The additional features that Alteryx needs to work on to make it more competitive include better collaboration and easier integration through API.
The price is very high, with licensing typically starting around five thousand dollars plus user per year.
We found excellent use cases for automation through Alteryx, which provided the means to reduce operational costs and streamline the build of ETL pipelines without extensive coding.
Alteryx is more cost-effective compared to Informatica licenses, offering savings.
Alteryx not only represents data but also supports decision-making by suggesting the next steps.
Analysts who do not have any coding experience can still work on the transformation and preparation of data, which is quite useful.
Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau.
| Product | Mindshare (%) |
|---|---|
| Alteryx | 3.7% |
| Darwin | 1.5% |
| Other | 94.8% |

| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 16 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Large Enterprise | 2 |
Alteryx provides user-friendly, no-code tools for data blending, preparation, and analysis. Its drag-and-drop interface and in-database capabilities simplify integration with data sources while maintaining data integrity.
Alteryx offers a comprehensive suite for automation of data workflows, reducing manual tasks and enhancing processing efficiency. Known for robust predictive and spatial analytics, it effectively handles large datasets. The platform's flexibility allows for custom script deployments, supported by a strong community. However, Alteryx faces challenges with high pricing, lack of cloud support, and limited data visualization tools. Users express a need for more in-built data science functionalities, improved API integration, and a smoother learning curve. Connectivity and documentation gaps, along with complex workflows, are noted concerns, suggesting areas for enhancement. Alteryx is widely used for tasks like ETL processes, data preparation, predictive modeling, and report generation, supporting functions like financial projections and spatial analysis.
What features define Alteryx?Alteryx is implemented across industries for diverse needs such as anomaly detection in finance, customer segmentation in marketing, and tax automation in auditing. Teams leverage its capabilities for data blending and predictive modeling to enhance operational efficiency and address specific business needs effectively.
Darwin offers advanced features like automated model-building, data cleaning, and rapid iteration, designed for efficient and intuitive use, enhancing productivity through easy system integration and model optimization.
Darwin caters to enterprises needing robust data management and streamlined model development. It provides tools for evaluating dataset quality and resolving data issues such as missing entries or incorrect types. With its REST API, it integrates seamlessly into existing systems, empowering rapid model optimization. While users find its interface intuitive, there is a demand for more advanced functionalities such as direct data access through APIs and enhancements in non-supervised models. The platform's educational resources and transparency in operations are areas identified for further improvement, along with user-friendly enhancements to dashboards.
What are Darwin's Most Important Features?Darwin is instrumental in industries like lending, where it's used for predicting credit defaults and managing risk portfolios. It supports client segmentation and delinquency assessment, allowing firms to analyze data for preemptive actions. Additionally, it's effective in sectors such as oil, gas, and aerospace for data analysis, supply chain optimization, and model creation, promoting efficient processes and reducing dependence on specialist skills.
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.