

Anaconda Business and Dataiku compete in the data science platform space, each with unique strengths. Anaconda Business has an upper hand in cost-effectiveness due to its open-source nature and extensive library support, while Dataiku stands out with MLOps and integration capabilities catering to large enterprises.
Features: Anaconda Business offers an extensive set of libraries, swift environment setup, and robust package management. It includes pre-built packages and integrates tools like Jupyter Notebook, providing ease for both beginners and professionals. Dataiku focuses on MLOps and no-code data preparation tools, appealing to non-coders. Its integration with public cloud services and automation features are tailored for enterprise environments.
Room for Improvement: Anaconda users seek better support on open-source operating systems and improved documentation for on-premise setups, alongside a more intuitive interface. They also desire integration with emerging tech libraries like computer vision and enhanced stability. Dataiku faces critiques for a high price and limited GitHub integration. It could improve flexibility in code-based components and support for complex data types while addressing pricing concerns and expanding collaborative features.
Ease of Deployment and Customer Service: Both Anaconda Business and Dataiku provide flexible deployment options, including on-premises and private cloud capabilities. Anaconda users praise its extensive community support and documentation, allowing for problem-solving without direct technical support. Dataiku also offers strong deployment options and benefits from thorough documentation, with users mostly relying on community resources.
Pricing and ROI: Anaconda Business is noted for being cost-effective due to its open-source model, appealing to budget-conscious users needing extensive libraries. It often yields a high ROI due to time and cost savings in development. Conversely, Dataiku's higher price can limit accessibility for smaller organizations but provides substantial ROI in large enterprise settings by boosting productivity and efficiency.
Everyone being able to work smoothly without unnecessary delays.
I have seen a return on investment; specifically, when we talk about efficiency, it's both time-saving and money-saving.
I have seen a return on investment with time saved by 50% and less downtime, allowing the team to deliver projects faster with fewer errors.
The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.
In terms of ROI, the use of Dataiku simplifies the architecture of customers, which helps them to decommission some of their existing tools;
Anaconda Business customer support is very active with a quick response time.
Overall, support was reliable when we needed it, just not super-fast every single time.
The customer support for Anaconda Business provides a better approach.
Dataiku partners with local industry experts who understand the business better and provide support.
The support team does not provide adequate assistance.
As a partner with Dataiku, my experience with them is good; they are supportive, and when we contact them, we receive a quick response.
As more environments or users get added, it still runs smoothly without major slowdowns.
Anaconda Business scales very well because it is built around centralized environment and package management.
Anaconda does not have scalability restrictions as it depends on the type of machine running it.
Earlier, setting up or troubleshooting conflicts could take anywhere from thirty minutes to an hour, but now most setups just work.
In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.
It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much.
They should enhance the security point of view; it's good, but it needs some more advanced features.
The pricing should be a little lower for a single person to use, as it might be affordable for an organization, but for my single use, it is difficult.
Someone who needs to do coding can do it, and someone who does not know coding can also build solutions.
The license is very expensive.
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.
Anaconda is an open-source tool, so I do not pay anything for it.
My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.
My experience with pricing, setup cost, and licensing indicates that it is a bit costly, but it is useful.
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.
Anaconda Business has positively impacted my organization because, when discussing the security point of view, it's exceptional; when comparing it to other solutions, Anaconda Business is superior.
We find the advanced security, governance, and collaborative features for organizations using Python and R particularly useful.
Anaconda Business positively impacts our organization by protecting us from compliance and security risks while keeping the environment consistent, allowing our team to focus on insight and innovation instead of worrying about setups, security, and software issues.
This feature is useful because it simplifies tasks and eliminates the need for a data scientist.
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.
It offers most of the capabilities required for data science, MLOps, and LLMOps.
| Product | Market Share (%) |
|---|---|
| Dataiku | 9.3% |
| Anaconda Business | 2.5% |
| Other | 88.2% |

| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 2 |
| Large Enterprise | 19 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 2 |
| Large Enterprise | 8 |
Anaconda Business provides a comprehensive platform for data science applications, integrating extensive libraries and seamless Python and R compatibility, enhancing developer productivity.
Anaconda Business offers data science professionals a platform combining extensive library support with pre-built models and seamless integration of Python and R environments. With features like a user-friendly interface and integrated Jupyter Notebook, it facilitates real-time code execution and debugging. Environmental management is simplified via Conda, while cloud-based access and package management enhance user experience. Community support and integration with applications like RStudio and Jupyter aid in data science and deep learning tasks.
What are the key features of Anaconda Business?Anaconda Business is widely used in industries like machine learning and data analysis, where it's employed for tasks such as predictive modeling and data visualization. Organizations utilize its compatibility with tools like Scikit-learn and TensorFlow for creating statistical models, supporting applications in fields such as analytics, education, subrogation, and warehouse management.
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.
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