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Anaconda

Anaconda

Overview

What is Anaconda?

Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research.…

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Recent Reviews

TrustRadius Insights

Anaconda is a versatile tool that has found widespread use across various departments and teams within organizations. It is highly …
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TrustRadius Insights
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Data Transformations (25)
    9.6
    96%
  • Visualization (24)
    9.6
    96%
  • Extend Existing Data Sources (23)
    8.9
    89%
  • Interactive Data Analysis (23)
    8.9
    89%
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Pricing

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Free Tier

$0

Cloud
per month

Starter Tier

$9

Cloud
per month

Business Tier

$50

Cloud
per month per user

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visitwww.anaconda.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Product Demos

Introducing Anaconda Distribution for Python in Excel

YouTube

Introducing: Anaconda Assistant

YouTube

Anaconda for Open-Source Security with Python and R

YouTube

AI Development in the Enterprise with Anaconda's Data Science Platform

YouTube
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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

9.4
Avg 8.5

Data Exploration

Ability to explore data and develop insights

9.2
Avg 8.4

Data Preparation

Ability to prepare data for analysis

9.4
Avg 8.2

Platform Data Modeling

Building predictive data models

9.3
Avg 8.5

Model Deployment

Tools for deploying models into production

9.5
Avg 8.6
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Product Details

What is Anaconda?

Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.


Anaconda Features

Platform Connectivity Features

  • Supported: Extend Existing Data Sources

Data Exploration Features

  • Supported: Visualization
  • Supported: Interactive Data Analysis

Data Preparation Features

  • Supported: Data Transformations
  • Supported: Data Encryption

Platform Data Modeling Features

  • Supported: Multiple Model Development Languages and Tools
  • Supported: Automated Machine Learning
  • Supported: Single platform for multiple model development
  • Supported: Self-Service Model Delivery

Model Deployment Features

  • Supported: Flexible Model Publishing Options
  • Supported: Security, Governance, and Cost Controls

Anaconda Integrations

Anaconda Competitors

Anaconda Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo
Supported CountriesGlobal

Frequently Asked Questions

Dataiku, Domino Enterprise MLOps Platform, and Posit are common alternatives for Anaconda.

Reviewers rate Connect to Multiple Data Sources highest, with a score of 9.8.

The most common users of Anaconda are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(143)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Anaconda is a versatile tool that has found widespread use across various departments and teams within organizations. It is highly regarded by users for its ability to import libraries, train predictive algorithms, and estimate value sources. This makes it an invaluable tool for data scientists and machine learning engineers who rely on it for real-world problem-solving and project development. Anaconda's package management system is particularly appreciated as it helps maintain up-to-date Python libraries, saving time and avoiding installation issues. Additionally, its cross-platform program facilitates seamless collaboration among Mac/PC/Linux users.

One of the key use cases of Anaconda is in the field of business intelligence and data science. Professionals in this domain utilize Anaconda for analysis, forecasting, and answering critical questions. Organizations also leverage Anaconda to identify the impact of COVID-19 on different products by analyzing customer survey data. The software's robust capabilities make it an ideal choice for managing large-scale projects with multiple dependencies, ensuring reproducibility of analysis, and providing a standardized working environment. Furthermore, Anaconda serves as a comprehensive data analysis environment, particularly when coupled with the user-friendly Jupyter Notebook.

In addition to its applications in data science and business intelligence, Anaconda finds utility in other areas such as banking departments for coding complex tasks like risk prediction and evaluation. It also supports software development objectives by enabling quick setup of development environments for employees. The product is widely used in analytics-based projects, including building small applications with Spyder and reporting and visualization with R and Orange. Moreover, researchers in fields like engineering and geoscience often turn to Anaconda as a research platform for prototyping custom algorithms and sharing progress with teammates.

Overall, Anaconda proves itself as an indispensable tool that streamlines coding workflows, ensures version control, enhances collaboration among teams, simplifies package management, enables efficient scripting in Python, offers a wide range of libraries and packages for various domains, automates routine tasks like excel sheet modifications, and provides a robust environment for data analysis and visualization.

Anaconda as a one-stop destination: Many users have found Anaconda to be a convenient and comprehensive solution for data science and programming tools. It has been praised by multiple reviewers for providing important tools such as Jupyter, Spyder, and R in one platform.

User-friendly interface: The simplicity and ease of use of Anaconda's user interface have been appreciated by many reviewers. They have found it intuitive and easy to navigate through files in Jupyter, as well as install new libraries.

Flexibility in working with Python environments: Users have highlighted the flexibility of Anaconda in working with multiple Python environments based on their requirements. This feature has been found useful for different use cases by several reviewers.

  1. Slow performance and high resource consumption: Several users have expressed frustration with the slow performance of Anaconda, particularly when it comes to bootstrapping the software and loading its contents. Additionally, some reviewers have mentioned that Anaconda can consume a significant amount of RAM, making it unsuitable for large projects or older machines.

  2. Difficulty in installing packages and libraries: Many users have encountered challenges when installing specific Python libraries using Anaconda's package manager, conda. Some reviewers had to uninstall and reinstall Anaconda multiple times to resolve issues with library installation. Others found it confusing to work with Anaconda alongside other Python packages and versions on their machine.

  3. Lack of support and technical troubleshooting difficulties: A number of users have mentioned the lack of support for the free version of Anaconda, making it difficult to troubleshoot issues without technical assistance. Reviewers felt frustrated when encountering software crashes while running code in Anaconda, leading to data loss. They also expressed dissatisfaction with the irregular security updates and the lack of integration with version control tools.

Users commonly recommend Anaconda as an excellent IDE tool for Python developers. They appreciate its user-friendly interface and the positive coding experience it provides. Users also find it easy to manage libraries in different programming languages. Additionally, they value the availability of helpful training materials and tutorials, particularly for beginners in data science and machine learning. As a result, users suggest starting with Anaconda for beginners and using it for projects involving Python programming. Furthermore, they recommend considering PyCharm as a more sophisticated IDE alternative.

Attribute Ratings

Reviews

(1-25 of 37)
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July 05, 2022

The best and easiest data analysis tool

Ammar Aboalrub | TrustRadius Reviewer
Ammar Aboalrub
Freelancer
Self Employed (Computer Software, 1-10 employees)
Score 10 out of 10
Vetted Review
Verified User
Likelihood to Recommend
We said Anaconda for Python does data science activities, Anaconda for Python does it perfectly, and it's open-source too, Anaconda includes many very suitable for beginners standard data science packages and science libraries inside. It is easy to install on any operating system you want, and it is considered the best data science version control tool at present.
October 07, 2021

Best IDE for Data Science Projects

Zayed Rais | TrustRadius Reviewer
Zayed Rais
Program Analyst
Cognizant (Information Technology & Services, 10,001+ employees)
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is well suited for data science projects. If you are working with multiple projects, it [is] easy to build different environments for the requirements of the project. Easy interaction with [the] notebook for data collection, pre-processing, transforming, training, and visualizing. Sometimes, we are unable to update the libraries due to some security patches.
September 11, 2021

Anaconda - a platform made for Py.

Verified User
Contributor in Engineering
Oil & Energy Company, 10,001+ employees
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
A must-try for smaller data analytics teams who seek project reproducibility, multiple language support and extensive community support. For bigger teams, consider the enterprise version, which makes it easy for app, API deployment, authentication, custom repository, and sharing of work spaces.
September 09, 2021

Awesome tool for Data Scientists

Jay Thakkar | TrustRadius Reviewer
Jay Thakkar
Student
PP Savani University (Computer Software, 201-500 employees)
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Started with learning Python through Jupytor Notebook.
I have used Anaconda for image processing application making.
In which I have used Spyder and include many libraries of image processing.
Debugging of code made easy through it.
Auto suggestions in spyder are great to write code fast and efficiently.
You can observe the memory space required for your file through it.
June 28, 2021

Anaconda Review

Dilip Jain | TrustRadius Reviewer
Dilip Jain
Senior Database Administrator
Wedvyah (Entertainment, 51-200 employees)
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
To design an end-to-end solution or machine learning model, Anaconda is the one that can easily manage all the libraries and we can set the environment according to the project requirement. Anaconda is the best data science version control tool in the present time. This is the best solution that is packed with lots of ideas and good features. But in the case of designing the analytics dashboards and all then we give less priority to Anaconda but we can use analytics tools like Tableau or PowerBI.
June 25, 2021

One stop data science destination - Anaconda

RV
Rounak Verma
Data Analyst
Shipt (Retail, 5001-10,000 employees)
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
As a Data Analyst, it is my job to analyze large datasets using complex mathematical models. Anaconda provides a one-stop destination with tools like PyCharm, Jupyter, Spyder, and RStudio. One case where it is well suited is for someone who has just started his/her career in this field. The ability to install Anaconda requires zero to little skills and its UI is a lot easier for a beginner to try. On the other hand, for a professional, its ability to handle large data sets could be improved. From my experience, it has happened a lot that the system would crash with big files.
June 22, 2021

Powerful environment to work on what you want with what you want (not ironic!)

Gabriel Krahn | TrustRadius Reviewer
Gabriel Krahn
Analista de Suporte de Sistemas
T-Systems do Brasil (Computer Software, 10,001+ employees)
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is a good choice when you have to build different environments to perform different tasks (for example, one environment with Python 3.7 + TensorFlow and the other with Julia + TensorFlow.jl or even Flux). The fact that it supports an easy switch between different environments (if you ignore the part about your installation getting bigger and bigger) is a big win situation.
June 15, 2021

Complete Data Science software suit.

Verified User
Consultant in Information Technology
Outsourcing/Offshoring Company, 10,001+ employees
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
This will suit to any kind of work now days. We have built many data science applications using Anaconda Navigator. This is very easy to use and can be used for any work. We have used it for Image processing projects and worked very much accurately as we were able to install all the latest packages.
June 12, 2021

Anaconda for Data Science!

AC
Anomita Chandra
Business Analyst
University of Texas at Dallas (Information Technology & Services, 1001-5000 employees)
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Being a Data Science and Analyst professional Anaconda is the go to place for all the softwares.
Easy to access Jupyter, RStudio and gives direct access to your files in your PC. It is compatible to install as many libraries required for the work you do. I have worked with large live data for a project on RStudio and it let me easily connect to it, though the system crashed sometimes when I tried to execute the entire code but it always created a recovered file of the changes I made. So that was one of the features I really liked.
May 21, 2021

Hemant's review of Anaconda

Verified User
C-Level Executive in Product Management
Entertainment Company, 1-10 employees
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
[Anaconda] is appropriate if you have a employee force of more than ten people it helps in automating the work of setting up the systems so that people can work. It is very helpful and reduces a lot of time which is wasted on doing something which is not productive.
May 16, 2021

Data Science and Anaconda

Fernanda Ministerio | TrustRadius Reviewer
Fernanda Ministerio
Specialist
SENAI-DN (Non-profit Organization Management, 10,001+ employees)
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend

When choosing Python or R for software development, you choose a large language ecosystem with a wide variety of packages covering all programming needs. But in addition to libraries for everything from GUI development to machine learning, you can also choose from a variety of tool runtimes and their libraries; some runtimes may be more suited to the use case you have at hand than others.

Anaconda has versions optimized for special use cases. Anaconda was designed for Python developers who need a distribution supported by a commercial provider and with support plans for companies. The main use cases for Anaconda Python are mathematics, statistics, engineering, data analysis, machine learning, and related applications.

Anaconda groups together many of the most common libraries for commercial and scientific work in Python--SciPy, NumPy, Numba, and so on--and makes it much more personalized through a package management system.

Anaconda stands out from the other distributions for the way it integrates all these pieces. When installed, Anaconda offers a desktop application--Anaconda Navigator--that makes all aspects of the Anaconda environment available through a convenient user interface. Finding components, customizing them, and working with them is much easier with Anaconda than with CPython.

Another benefit is the way Anaconda handles components from outside the Python ecosystem, if they are prioritized for a specific package. Conda conda packages, created specifically for Anaconda, deal with the installation of Python packages and external third-party software requirements.

Since Anaconda includes so many useful libraries and can install even more with just a few keys, the size of an Anaconda installation can be much larger than that of other competitors. This can be an issue in situations where you have resource constraints.

May 10, 2021

Big guns for big scale projects: Anaconda

Verified User
Employee in Information Technology
Information Technology & Services Company, 1-10 employees
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is definitely good when it comes to large-scale projects in python requiring different versions of python as a dependency on project packages and use cases. It consumes heavy memory and is not suitable for smaller projects and is likely overkill for the same. If the user is new to anaconda, it takes time to get comfortable with it.
April 30, 2021

Anaconda for beginner data scientists!

Verified User
Engineer in Information Technology
Financial Services Company, 201-500 employees
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is great for setting a standard development environment for beginners. it is a very complete base deployment and does not require anything else to start running some basic datascience packages. while it allows you to install the packages via 'conda' the packages are not always the latest compared to pip.
April 16, 2021

Review for Anaconda

Tigran Petrosyan | TrustRadius Reviewer
Tigran Petrosyan
Risk Management Specialist
ACBA-CREDIT AGRICOLE BANK (Banking, 5001-10,000 employees)
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda have a lot of scientific libraries of Python which I use in my everyday work (Pandas, Numpy, Seaborn, matplotlib, etc). Jupiter Notebook is a best option for me if I have small tasks or small projects which I must do using Python. However if I have large projects I prefer to use PyCharm.
May 02, 2020

Easily share code with other departments

Verified User
Engineer in Manufacturing
Electrical & Electronic Manufacturing Company, 51-200 employees
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda (specifically Jupyter Notebook) is well suited for sharing code with other teams that are less programming-focused. It is very easy for me to open a pre-written code notebook, enter some values in the initial inputs box, press Run, and see my results. It is simple enough to open the notebook, and run the code, so we can use it in our production area and train the assembly technicians on how to operate it. If the code is properly written, it is easy to know when something went wrong.
March 17, 2020

Good way to standardize Python-based developments & support for desktop users.

Juande Santander-Vela | TrustRadius Reviewer
Juande Santander-Vela
Software Development Lead / Product Manager at Solution Level
SKA Organisation (Research, 51-200 employees)
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda, and Miniconda, are easy to deploy, scientifically-ready Python distributions, especially well-suited for the fields of science, astronomy, and engineering. We are using Miniconda for finer-grained customization of environments in containers for deployment.

We are not using the customer supported version of Anaconda, and instead, we are relying on the community edition, based on the Open Source of all of our software. Hence, I am not evaluating Anaconda's support. Also, we are not making use as a company of the multi-language support in Anaconda, but I have tried the SciJava, R, and Julia support in Anaconda.
February 28, 2020

Anaconda: A data scientist's best friend

Verified User
Analyst in Professional Services
Financial Services Company, 10,001+ employees
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is the best data science version control tool in the market. With Anaconda, you can easily create, remove, and switch environments to run different scripts. What is more, you can also use it to export the current environment automatically into yaml file that can be used to recreate the same environment.
February 18, 2020

Anaconda - The tool to master for Python based data analytic tasks

Verified User
Strategist in Information Technology
Package/Freight Delivery Company, 10,001+ employees
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is very suitable for a research team/lab/department which has many data scientists who want to apply some Python-based analytic programming and want to cooperate in sharing the results easily. It is not very well suited for final production environment deployment.
February 14, 2020

Anaconda is the best distribution which includes all in one

Verified User
Engineer in Research & Development
Education Management Company, 501-1000 employees
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Likelihood to Recommend
Anaconda is an all-in-one package. It is free and easy to install in any operating system. I'm using Anaconda in physics and engineering-related results. It is very suitable in data analysis too. You can work with big data in a very simple way. It has Spyder, Jupyter and many more installed in one platform. Jupyter Notebook is very nice feature in Anaconda. I believe it is appropriate for every problem and in every field.
January 22, 2020

All-in-one data science package

Verified User
Professional in Research & Development
Consumer Electronics Company, 5001-10,000 employees
Score 10 out of 10
Vetted Review
Verified User
Likelihood to Recommend
For anyone who's starting data analytics, Anaconda is great because you don't have to deal with installing and knowing all these Python and R packages yourself. Moreover, you learn them as you start using them via Anaconda. If you're going to read, manipulate, preprocess, and write data, Anaconda is great. If you need data visualization, Anaconda has Jupyter Notebook, as well as Matplotlib, and Seaborn. If you need forecasting and prediction, whether it is classification or regression or even unsupervised learning, Anaconda provides the Sci-kit Learn library. Furthermore, you can install Catboost, XGBoost, LGBM via Anaconda, which uses the Sci-kit Learn interface.
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