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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
11th
Average Rating
8.2
Reviews Sentiment
7.4
Number of Reviews
19
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 April 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 18.2%, down from 19.1% 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

"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."
"It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations."
"The most advantageous feature is the logic building."
"The virtual environment is very good."
"Voice Configuration and Environmental Management Capabilities are the most valuable features."
"The solution is stable."
"I can use Anaconda for non-heavy tasks."
"The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"Easy to use and requires minimal coding and customizations."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"It's easy to increase performance as required."
"We can scale the product."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
 

Cons

"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."
"A lot of people and companies are investing in creating automated data cleaning and processing environments. Anaconda is a bit behind in that area."
"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."
"Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring."
"Anaconda can't handle heavy workloads."
"Anaconda should be optimized for RAM consumption."
"The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools."
"It would be great if Databricks could integrate all the cloud platforms."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"Would be helpful to have additional licensing options."
 

Pricing and Cost Advice

"The product is open-source and free to use."
"The tool is open-source."
"The licensing costs for Anaconda are reasonable."
"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"My company uses the free version of the tool. There is also a paid version of the tool available."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."
"I would rate Databricks' pricing seven out of ten."
"The solution is affordable."
"The solution is a good value for batch processing and huge workloads."
"Price-wise, I would rate Databricks a three out of five."
"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
9%
Government
8%
Manufacturing Company
8%
Financial Services Firm
17%
Computer Software Company
10%
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...
 

Comparisons

 

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: April 2025.
848,989 professionals have used our research since 2012.