We performed a comparison between Anaconda and Databricks based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."I can use Anaconda for non-heavy tasks."
"The most advantageous feature is the logic building."
"The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages."
"The virtual environment is very good."
"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"The initial setup phase of Databricks was good."
"It's easy to increase performance as required."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The processing capacity is tremendous in the database."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"It is a cost-effective solution."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"Anaconda can't handle heavy workloads."
"When you install Anaconda for the first time, it's really difficult to update it."
"One feature that I would like to see is being able to use a different language in a different cell, which would allow me to mix R and Python together."
"The solution would benefit from offering more automation."
"One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known."
"It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"I believe that this product could be improved by becoming more user-friendly."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"The integration and query capabilities can be improved."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
Anaconda is ranked 13th in Data Science Platforms with 15 reviews while Databricks is ranked 1st in Data Science Platforms with 78 reviews. Anaconda is rated 7.8, while Databricks is rated 8.2. The top reviewer of Anaconda writes "Offers free version and is helpful to handle small-scale workloads". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Anaconda is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Microsoft Power BI, IBM SPSS Statistics and IBM Watson Studio, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio.
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