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Anaconda is a versatile tool that has found widespread use across various departments and teams within organizations. It is highly …
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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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Popular Features
- Data Transformations (25)9.696%
- Visualization (24)9.696%
- Extend Existing Data Sources (23)8.989%
- Interactive Data Analysis (23)8.989%
Pricing
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
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
Features
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Product Details
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- Integrations
- Competitors
- Tech Details
- FAQs
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 Competitors
Anaconda Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux, Mac |
| Mobile Application | No |
| Supported Countries | Global |
Frequently Asked Questions
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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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!
- Business Problems Solved
- Pros
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- Recommendations
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.
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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.
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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.
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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
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July 05, 2022
The best and easiest data analysis tool
Score 10 out of 10
Vetted Review
Verified User
There are several reasons why Anaconda is better to use for me including that it is much easier to use than Baycharm. Also, the user interface is not as complicated as that of Baycharm. Even Anaconda does not slow down my device, using PaySharm slowed down my device in an indescribable way.
November 05, 2021
Anaconda: Best IDE for Python
It provides several IDEs like Spyder and Jupiter that would be enough for me to write my Python script. You can easily install it on a Windows or Linux computer and supports many libraries.
October 07, 2021
Best IDE for Data Science Projects
In Anaconda, [it is easy] to find and install the required libraries. Here, we can work on multiple projects with different sets of the environment. [It is] easy to create the notebook for developing the ML model and deployment. Right now, it is the best data science version control tool in the IT software market.
September 11, 2021
Anaconda - a platform made for Py.
- RStudio and Dataiku DSS
Suitable for Python development where there’s internal supporting for Python; otherwise, other platform offers similar capabilities with lower cost.
September 09, 2021
Awesome tool for Data Scientists
- Microsoft Visual Studio Code, Notepad++ and Sublime Text
I have used many other tools for coding purposes.
But for python programming, the best fit tool is Anaconda.
Memory management is best in Anaconda.
The user interface is simple to compare to other tools.
We can know how many libraries are included and keep track of that.
Overall it is a great tool.
But for python programming, the best fit tool is Anaconda.
Memory management is best in Anaconda.
The user interface is simple to compare to other tools.
We can know how many libraries are included and keep track of that.
Overall it is a great tool.
June 28, 2021
Anaconda Review
On top of all the software that I have used, Anaconda is the best because in Anaconda we have built-in packages that provide no headache to install packages and we can design a separate environment for different projects. Anaconda has versions made for special use cases. Anaconda is designed for Python developers who need distribution supported by a commercial provider and corporate sponsorship programs. Major cases of Anaconda Python usage statistics, statistics, engineering, data analysis, machine learning, and related applications. Another advantage is the way Anaconda handles items from outside the Python ecosystem when they are prioritized in a particular package. Conda packages, designed specifically for Anaconda, address the installation of Python packages and external software requirements.
June 25, 2021
One stop data science destination - Anaconda
One of the main competitors to Anaconda can be Google products such as Colab. Colab gives you the flexibility to handle large datasets gives it an edge over Anaconda. But again, the ease of access and usability of Anaconda stacks up against Colab. Besides, Anaconda relies more on your machine which makes it safe to use.
June 15, 2021
Complete Data Science software suit.
This is an open source tool and used very easily. All the notebooks are under one navigator solved the whole problem.
June 12, 2021
Anaconda for Data Science!
Anaconda has features which overpowers it over the other analytical tools I have used. Also it provides multiple ways to reach to the solution, depending on the developers expertise. When I was a beginner at using Anaconda, since it is open source and the community using Anaconda is massive it was easy to find solutions and help to my errors.
May 21, 2021
Hemant's review of Anaconda
May 16, 2021
Data Science and Anaconda
Some analyzed tools, such as PyCharm and Spyder, are simpler to use but still do not have all the libraries needed for those starting out in data science--or in institutions that need to grow in that direction. Anaconda is more robust but stable, more complete, and the usability is very good for professionals. Anaconda is also more popular and user groups often exchange information and codes generated in Anaconda. This makes it easier to find information, other libraries, and learning in general for companies that are starting their data science processes.
May 10, 2021
Big guns for big scale projects: Anaconda
If the project is not large scale then Jupiter notebooks or Visual Studio Code serve well. If you don't have any dependency on Python versions, these IDEs can be well suited for fast development and deployment.
April 30, 2021
Anaconda for beginner data scientists!
Anaconda includes many standard data science packages where as the regular python installation does not.
Depending on use case, some may feel Anaconda may be "bloated"
For ease Anaconda is better, for minimizing extraneous package installation, the regular python installer is better
Anaconda is great for a beginner data scientist
Depending on use case, some may feel Anaconda may be "bloated"
For ease Anaconda is better, for minimizing extraneous package installation, the regular python installer is better
Anaconda is great for a beginner data scientist
April 16, 2021
Review for Anaconda
I know that PyCharm is a IDE and Anaconda is a distribution. However I use Anaconda largely due to Jupyter Notebook, which more or less does the same job as PyCharm. 1 year ago I decided to use Anaconda (Jupiyer Notebook) as it is easier to use it as a beginner(at least my friends said so). Now I can verify that . Now I use Jupyter Notebook as I do not have large projects
May 02, 2020
Easily share code with other departments
I have not used another program like Anaconda before.
Anaconda has 64-bit support in the community edition, and package management is more in line with the way we think.
March 05, 2020
Anaconda provides a vast array of compilers and tools for every developer - and is easy enough for non-developers to setup.
MATLAB is more of a pay-as-you-go alternative, which not only does not use Python but is also more bloated and costly. MATLAB takes longer to install, setup, and configure for new users who may require specific packages - such as the Classification Learner (machine learning), Signal Processing Application, or Regression Learner application. Furthermore, far fewer developers recommend MATLAB in developing scientific applications compared to Python.
March 03, 2020
Anaconda turned a group into a team
Compare Anaconda to Unix coding system. You can use PIP to install and create requirement.txt to replace environment.yml to avoid using Anaconda. However, Anaconda is such an excellent tool to maintain your environment and check the version of your package and update the package whenever needed, which is not available elsewhere.
February 28, 2020
Anaconda: A data scientist's best friend
Anaconda is very strong in the environment and version control that make data science work much easier. The only thing that might be comparable to Anaconda would be using Kubernetes to control Docker. Another potential improvement would be replacing spyder with PyCharm and Atom in the software selection under Anaconda navigation.
February 18, 2020
Anaconda for Python
I like SpyDER, which comes with Anaconda better for its intuitive layout and variable explorer options.
January 22, 2020
All-in-one data science package
Score 10 out of 10
Vetted Review
Verified User
Anaconda gives freedom to do anything with its packages, compared to other non-programming language-based softwares. It is almost possible to do anything with Anaconda. Anaconda brings ease of integrity because it is possible to integrate anything with a Python Py script, compared to other low integrity software packages. Not to mention it is very easy to read from Databases with Anaconda. Overall it is the ability and freedom to do anything with Anaconda which caused us to choose and happily use it.
March 13, 2019
Anaconda: The Data Science Starter Kit.
I prefer Anaconda due to the control I have at every level over the data and the visualizations. Power BI does a better job at guessing what graphics to use, but these usually aren't the most helpful. Anaconda and the slew of Python extensions that add incredible functionality, make it much more powerful without such a steep learning curve as Power BI.
November 28, 2018
Anaconda - Flexible Enterprise Data Science Solution
Other systems might be easier to set-up but Anaconda is a fairly flexible analytics toolkit. It can be configured in a way that truly matches the way in which your business or analytics department works. Built on top of lots of open source projects so things aren't siloed and you can avoid vendor lock-in.
September 06, 2018
Anaconda as an analytics platform for beginners
Score 10 out of 10
Vetted Review
Verified User