Try our new research platform with insights from 80,000+ expert users

Anaconda vs Databricks comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Anaconda
Ranking in Data Science Platforms
12th
Average Rating
8.2
Reviews Sentiment
7.4
Number of Reviews
18
Ranking in other categories
No ranking in other categories
Databricks
Ranking in Data Science Platforms
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Streaming Analytics (1st)
 

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Anaconda is 2.1%, down from 2.2% compared to the previous year. The mindshare of Databricks is 18.5%, up from 18.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Rohan Sharma - PeerSpot reviewer
Provides all the frameworks and makes it easy to create environments for multiple projects
The best thing is that it provides all the frameworks and makes it easy to create environments for multiple projects using Anaconda. It is easy for a beginner to learn to use Anaconda. Comparatively, it is easier than using virtual environments or other environments because of the Conda environment. However, there are many things in Anaconda that people need to be aware of, so it can be challenging.
ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations."
"It helped us find find the optimal area for where our warehouse should be located."
"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 solution is stable."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"The documentation is excellent and the solution has a very large and active community that supports it."
"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 best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"There are good features for turning off clusters."
"Databricks has helped us have a good presence in data."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"Databricks' capability to process data in parallel enhances data processing speed."
"We have the ability to scale, collaborate and do machine learning."
"The main features of the solution are efficiency."
 

Cons

"The ability to schedule scripts for the building and monitoring of jobs would be an advantage for this platform."
"It also takes up a lot of space."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"Having a small guide or video on the tool would help learn how to use it and what the features are."
"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."
"The solution would benefit from offering more automation."
"I think better documentation or a step-by-step guide for installation would help, especially for on-premise users."
"Anaconda can't handle heavy workloads."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Would be helpful to have additional licensing options."
"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
 

Pricing and Cost Advice

"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"The product is open-source and free to use."
"The tool is open-source."
"My company uses the free version of the tool. There is also a paid version of the tool available."
"The licensing costs for Anaconda are reasonable."
"The billing of Databricks can be difficult and should improve."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"Databricks are not costly when compared with other solutions' prices."
"We're charged on what the data throughput is and also what the compute time is."
"The solution is based on a licensing model."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"The pricing depends on the usage itself."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
841,004 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
10%
Manufacturing Company
8%
University
8%
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Anaconda?
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.
What is your experience regarding pricing and costs for Anaconda?
Anaconda does not require a pricing structure, and it is available as an open-source tool. The features of Python, Jupyter, and others are free to use.
What needs improvement with Anaconda?
Anaconda consumes a significant amount of processing memory when working on it. This is something that needs improvement as it can impact performance.
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
 

Also Known As

No data available
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Find out what your peers are saying about Anaconda vs. Databricks and other solutions. Updated: January 2025.
841,004 professionals have used our research since 2012.