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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
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 February 2025, in the Data Science Platforms category, the mindshare of Anaconda is 2.1%, down from 2.3% compared to the previous year. The mindshare of Databricks is 18.8%, up from 18.5% 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."
"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."
"Voice Configuration and Environmental Management Capabilities are the most valuable features."
"It has a lot of functionality available, supports many libraries, and the developers are continually improving it."
"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 documentation is excellent and the solution has a very large and active community that supports it."
"The most advantageous feature is the logic building."
"The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code."
"In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."
"The setup is quite easy."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"It's very simple to use Databricks Apache Spark."
"Databricks integrates well with other solutions."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
 

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."
"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."
"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."
"Anaconda should be optimized for RAM consumption."
"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."
"Anaconda can't handle heavy workloads."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"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."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"The Databricks cluster can be improved."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"The integration of data could be a bit better."
 

Pricing and Cost Advice

"The product is open-source and free to use."
"My company uses the free version of the tool. There is also a paid version of the tool available."
"Anaconda is free to use, but in terms of hardware costs, you might need heavy GPUs to run CUDA and other demanding tasks."
"The licensing costs for Anaconda are reasonable."
"The tool is open-source."
"Price-wise, I would rate Databricks a three out of five."
"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."
"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."
"The price is okay. It's competitive."
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."
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Top Industries

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

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: January 2025.
838,640 professionals have used our research since 2012.