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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Anaconda

    Score8.8 out of 10
    N/AAnaconda is an enterprise Python platform that provides access to open-source Python and R packages used in AI, data science, and machine learning. These enterprise-grade solutions are used by corporate, research, and academic institutions for competitive advantage and research.

    $0

    per month

    Pricing
    Anaconda
    Editions & Modules
    Free Tier
    $0
    per month
    Starter Tier
    $15
    per month per user
    Business
    $50
    per month per user
    Custom
    Contact Sales
    Offerings
    Pricing Offerings
    Anaconda
    Free Trial
    No
    Free/Freemium Version
    Yes
    Premium Consulting/Integration Services
    Yes
    Entry-level Setup FeeNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    Anaconda
    Considered Both Products
    Anaconda
    Chose Anaconda
    I am using both; when it comes to application deployment on the server, I use Docker, and sometimes, I use Docker with conda image for deployment when it comes to ML/DL apps.
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Chose Anaconda
    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.
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Chose Anaconda
    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.
    Incentivized
    Chose 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 …
    Incentivized
    Chose Anaconda
    It is almost dishonest to compare Anaconda with PyCharm as they do different things in their basic forms unless you spend a lot of time configuring plugins on your PyCharm environment. Anaconda has a lot of things ready and you just need to install your libs and dependencies.
    Incentivized
    Chose Anaconda
    This is an open source tool and used very easily. All the notebooks are under one navigator solved the whole problem.
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Chose Anaconda
    Free ware, better design ease of use
    Incentivized
    Chose Anaconda
    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. …
    Incentivized
    Chose 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 …
    Incentivized
    Chose 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.
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Chose 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 …
    Incentivized
    Chose Anaconda
    Anaconda has 64-bit support in the community edition, and package management is more in line with the way we think.
    Incentivized
    Chose Anaconda
    I have not used another program like Anaconda before.
    Incentivized
    Chose Anaconda
    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), …
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Chose Anaconda
    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
    Incentivized
    Chose Anaconda
    I like SpyDER, which comes with Anaconda better for its intuitive layout and variable explorer options.
    Incentivized
    Chose Anaconda
    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, …
    Incentivized
    Chose Anaconda
    Suitable for Python development where there’s internal supporting for Python; otherwise, other platform offers similar capabilities with lower cost.
    Incentivized
    Chose Anaconda
    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, …
    Incentivized
    Chose Anaconda
    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 …
    Incentivized
    Key User Insights
    Would buy again
    96%
    Would buy again
    24 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    23 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    25 Answers
    Lived up to sales and marketing promises
    94%
    Lived up to sales and marketing promises
    15 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    21 Answers
    Features
    Anaconda
    Platform Connectivity
    Comparison of Platform Connectivity features of Anaconda
    Feature
    Anaconda
    9.3
    25 Ratings
    11% above category average
    Connect to Multiple Data Sources9.822 Ratings
    Extend Existing Data Sources8.024 Ratings
    Automatic Data Format Detection9.721 Ratings
    MDM Integration9.614 Ratings
    Data Exploration
    Comparison of Data Exploration features of Anaconda
    Feature
    Anaconda
    8.5
    25 Ratings
    1% above category average
    Visualization9.025 Ratings
    Interactive Data Analysis8.024 Ratings
    Data Preparation
    Comparison of Data Preparation features of Anaconda
    Feature
    Anaconda
    9.0
    26 Ratings
    9% above category average
    Interactive Data Cleaning and Enrichment8.823 Ratings
    Data Transformations8.026 Ratings
    Data Encryption9.719 Ratings
    Built-in Processors9.620 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Anaconda
    Feature
    Anaconda
    9.2
    24 Ratings
    8% above category average
    Multiple Model Development Languages and Tools9.023 Ratings
    Automated Machine Learning8.921 Ratings
    Single platform for multiple model development10.024 Ratings
    Self-Service Model Delivery9.019 Ratings
    Model Deployment
    Comparison of Model Deployment features of Anaconda
    Feature
    Anaconda
    9.5
    21 Ratings
    11% above category average
    Flexible Model Publishing Options10.021 Ratings
    Security, Governance, and Cost Controls9.020 Ratings
    Best Alternatives
    Anaconda
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Jupyter Notebook
    Score8.6 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternatives
    User Ratings
    Anaconda
    Likelihood to Recommend
    10.0
    (38 ratings)
    Likelihood to Renew
    7.0
    (1 ratings)
    Usability
    9.0
    (3 ratings)
    Support Rating
    8.9
    (9 ratings)
    User Testimonials
    Anaconda
    Likelihood to Recommend
    Anaconda
    I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
    Incentivized
    Read full review
    Pros
    Anaconda
    • Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
    • Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
    • Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
    Incentivized
    Read full review
    Cons
    Anaconda
    • It can have a cloud interface to store the work.
    • Compatible for large size files.
    • I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
    Incentivized
    Read full review
    Likelihood to Renew
    Anaconda
    It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
    Incentivized
    Read full review
    Usability
    Anaconda
    I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
    Incentivized
    Read full review
    Support Rating
    Anaconda
    Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
    Incentivized
    Read full review
    Alternatives Considered
    Anaconda
    I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
    Incentivized
    Read full review
    Return on Investment
    Anaconda
    • It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
    • By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
    • There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
    Incentivized
    Read full review
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