We performed a comparison between Anaconda and Databricks based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most advantageous feature is the logic building."
"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."
"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."
"The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results."
"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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"The most valuable feature is the set of libraries that are used to support the functionality that we require."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"It's easy to increase performance as required."
"The initial setup is pretty easy."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"The initial setup phase of Databricks was good."
"The most valuable feature is the ability to use SQL directly with Databricks."
"The solution would benefit from offering more automation."
"When you install Anaconda for the first time, it's really difficult to update it."
"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"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."
"I think that the framework can be improved to make it easier for people to discover and use things on their own."
"It also takes up a lot of space."
"Anaconda can't handle heavy workloads."
"The interface could be improved. Other solutions, like Visual Studio, have much better UI."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"A lot of people are required to manage this solution."
"Pricing is one of the things that could be improved."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"CI/CD needs additional leverage and support."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"Costs can quickly add up if you don't plan for it."
Anaconda is ranked 13th in Data Science Platforms with 17 reviews while Databricks is ranked 1st in Data Science Platforms with 78 reviews. Anaconda is rated 8.0, 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, Dremio and Microsoft Azure Machine Learning Studio. See our Anaconda vs. Databricks report.
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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.
