Anaconda vs. PyCharm

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Anaconda
Score 8.7 out of 10
N/A
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.
$0
per month
PyCharm
Score 9.0 out of 10
N/A
PyCharm is an extensive Integrated Development Environment (IDE) for Python developers. Its arsenal includes intelligent code completion, error detection, and rapid problem-solving features, all of which aim to bolster efficiency. The product supports programmers in composing orderly and maintainable code by offering PEP8 checks, testing assistance, intelligent refactorings, and inspections. Moreover, it caters to web development frameworks like Django and Flask by providing framework…
$9.90
per month per user
Pricing
AnacondaPyCharm
Editions & Modules
Free Tier
$0
per month
Starter Tier
$9
per month
Business Tier
$50
per month per user
Enterprise Tier
60.00+
per month per user
For Individuals
$99
per year per user
All Products Pack for Organizations
$249
per year per user
All Products Pack for Individuals
$289
per year per user
For Organizations
$779
per year per user
Offerings
Pricing Offerings
AnacondaPyCharm
Free Trial
NoYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AnacondaPyCharm
Considered Both Products
Anaconda
Chose Anaconda
Anaconda is way easier to set-up. On Anaconda we have users working on Machine Learning in minutes, where on PyCharm is takes a lot longer to set-up and often involves getting help from IT. PyCharm is easier to integrate with Code repositories (such as GitHub), so if that's …
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
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 …
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 …
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.
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 …
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 …
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. …
Chose Anaconda
Free ware, better design ease of use
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 …
Chose Anaconda
I like SpyDER, which comes with Anaconda better for its intuitive layout and variable explorer options.
Chose Anaconda
Anaconda is the best Python environment because you have all the things you need all in one places, at the reach of your hand. You can download and manage libraries as you wish and is very easy to create new projects and API's for all your stuff.

It's Multiplatform so you don't …
PyCharm
Chose PyCharm
What differentiates PyCharm from other products is that it is built for a particular language (Python) and works great while doing it, without losing efficiency with the rest of languages. It's simple, easy to use, fast and efficient, what else could you need?
Chose PyCharm
PyCharm is the best tool to switch between different projects. One can connect to various technologies at a time. Package and plugin installation is easy. Dark and light mode helps in working according to the mood. One can extend it to IntelliJ, depending on the need for custom …
Chose PyCharm
PyCharm was selected due to it's first class treatment of Python. Visual Studio is more general "Do everything" IDE which contains a lot of features our team didn't need. PyCharm strikes the balance of power and complexity.
Top Pros
Top Cons
TrustRadius Insights
AnacondaPyCharm
Highlights

TrustRadius
Research Team Insight
Published

PyCharm and Anaconda are both tools used to aid Python developers.  Though they are independent tools, PyCharm and AnaConda can be used together for projects that can benefit from both tools.  PyCharm is an IDE built to make it easier to write Python code, by providing a text editor and debugging, among other features.  Anaconda is a Python distribution focused on data driven projects. Both tools popular with businesses of all sizes that use Python.

Features and Limitations

PyCharm and Anaconda both provide specialized features for Python development, but provide different base functionalities.

PyCharm is an IDE, meaning it is interfaced with directly by developers writing Python code.  PyCharm provides a text editor including coding assistance features such as code navigation through search, and color coding.  Additionally, PyCharm provides support for multiple platforms, as well as complementary front end coding languages such as HTML and JavaScript.  In essence, PyCharm is designed to make it as easy as possible to code in Python, though it does not include any packages by default.  PyCharm also includes built-in support for Anaconda.

Anaconda includes a basic text editor, but its primary role is that of a Python distribution.  Projects using Anaconda can access data science packages of their choice from a library of over 400 popular packages.  Data science projects can use Anaconda to easily load packages to save time and reduce written code.  Anaconda is an ideal tool for performing data science tasks whether a business is using PyCharm or not, but it isn’t ideal for non-data oriented projects.

Pricing

PyCharm professional is priced at $199.00 per year, though its price reduces each year beyond the first. 

Anaconda is free to use for individuals, but pricing for teams starts at $10,000.  Enterprises that need unique features such as custom repositories can reach out to the vendor for a quote.

Features
AnacondaPyCharm
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.5
24 Ratings
12% above category average
PyCharm
-
Ratings
Connect to Multiple Data Sources9.822 Ratings00 Ratings
Extend Existing Data Sources8.923 Ratings00 Ratings
Automatic Data Format Detection9.621 Ratings00 Ratings
MDM Integration9.614 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
9.2
24 Ratings
9% above category average
PyCharm
-
Ratings
Visualization9.624 Ratings00 Ratings
Interactive Data Analysis8.923 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.4
25 Ratings
13% above category average
PyCharm
-
Ratings
Interactive Data Cleaning and Enrichment8.823 Ratings00 Ratings
Data Transformations9.625 Ratings00 Ratings
Data Encryption9.719 Ratings00 Ratings
Built-in Processors9.520 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.3
23 Ratings
9% above category average
PyCharm
-
Ratings
Multiple Model Development Languages and Tools9.622 Ratings00 Ratings
Automated Machine Learning8.921 Ratings00 Ratings
Single platform for multiple model development8.923 Ratings00 Ratings
Self-Service Model Delivery9.718 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Anaconda
9.5
20 Ratings
10% above category average
PyCharm
-
Ratings
Flexible Model Publishing Options9.620 Ratings00 Ratings
Security, Governance, and Cost Controls9.519 Ratings00 Ratings
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AnacondaPyCharm
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Score 9.3 out of 10
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User Ratings
AnacondaPyCharm
Likelihood to Recommend
9.5
(37 ratings)
7.8
(38 ratings)
Likelihood to Renew
7.0
(1 ratings)
10.0
(1 ratings)
Usability
9.0
(2 ratings)
-
(0 ratings)
Support Rating
8.9
(9 ratings)
8.3
(13 ratings)
User Testimonials
AnacondaPyCharm
Likelihood to Recommend
Anaconda
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.
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JetBrains
It's easy to create virtual environments and install packages for different projects as we may need project-specific packages for doing our experiments, also it's easy to see what changes we have made and create pull requests faster. But sometimes we want some light python editor like Jupiter notebook as PyCharm is relatively heavier, also Jupiter notebooks are a good option when we need to run remote code on local machines.
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Pros
Anaconda
  • It provides easy access to software like Jupyter, Spyder, R and QT Console etc.
  • Easy installation of Anaconda even without much technical knowledge.
  • Easy to navigate through files in Jupyter and also to install new libraries.
  • R Studio in Anaconda is easy to use for complex machine learning algorithms.
Read full review
JetBrains
  • Git integration is really essential as it allows anyone to visually see the local and remote changes, compare revisions without the need for complex commands.
  • Complex debugging tools are basked into the IDE. Controls like break on exception are sometimes very helpful to identify errors quickly.
  • Multiple runtimes - Python, Flask, Django, Docker are native the to IDE. This makes development and debugging and even more seamless.
  • Integrates with Jupyter and Markdown files as well. Side by side rendering and editing makes it simple to develop such files.
Read full review
Cons
Anaconda
  • Although I have generally had positive experiences with Anaconda, I have had trouble installing specific python libraries. I tried to remedy the solution by updating other packages, but in the end, things got really messed up, and I ended up having to uninstall and reinstall a total of about 4 times over the past 2 years.
  • If you have the free version of Anaconda, there is not much support. Googling questions and error messages are helpful, but there were times when I wished I would have been able to ask technical support to help me troubleshoot issues.
  • There were a few times when I tried to install tensorflow and tensorboard via Anaconda on a PC, but I could not get them to install properly. Anaconda allows you to create 'environments' , which allow you to install specific versions of python and associated libraries. You can keep your environments separate so they do not conflict with one another. Anyway, I ended up having to create several 'conda envrionments' just so I could use tensforflow/tensorboard and a few other utilities to avoid errors. This was somewhat annoying, because every time I wanted to run a specific model, I'd have to open up the specific conda environment with the appropriate python libraries.
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JetBrains
  • The biggest complaint I have about PyCharm is that it can use a lot of RAM which slows down the computer / IDE. I use the paid version, and have otherwise found nothing to complain about the interface, utility, and capabilities.
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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.
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JetBrains
It's perfect for our needs, cuts development time, is really helpful for newbies to understand projects structure
Read full review
Usability
Anaconda
The interface is an easy to use command-line interface, or a GUI for launching and/or discovering different parts of the system.
Read full review
JetBrains
No answers on this topic
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.
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JetBrains
I rate 10/10 because I have never needed a direct customer support from the JetBrains so far. Whenever and for whatever kind of problems I came across, I have been able to resolve it within the internet community, simply by Googling because turns out most of the time, it was me who lacked the proper information to use the IDE or simply make the proper configuration. I have never came across a bug in PyCharm either so it deserves 10/10 for overall support
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Alternatives Considered
Anaconda
ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics. Anaconda VS. MicroStrategy Analytics: Compared with Anaconda, MicroStrategy Analytics is very difficult to use and counter-intuitive Anaconda VS. Power BI For Office 365: One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Read full review
JetBrains
PyCharm is the best IDE for python development. PyCharm offers various features: source code completion, support for unit testing, integration with Docker/GitLab/Git, ability to manage and configure virtual environments, auto-indentation, and re-factoring code with ease. Support for JSON/Shell scripts and support for Flask/Django Other tools are effective for creating isolated scripts but not for handling projects with more than two scripts.
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Return on Investment
Anaconda
  • Positive: Lower maintenance cost compared to other tools on the market
  • Positive: Ease in hiring professionals already accustomed to the tool in the job market
  • Positive: Projects are portable, allowing you to share projects with others and execute projects on different platforms, reducing deployment costs
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JetBrains
  • Buying the licensed pro version is a bit costly, but overall because of its features and its speed, the time taken by a developer to develop something can be improved. Indirectly getting a good return of Investment.
  • Considering the team size and its features, one can go for the licensed version as the ROI is high.
  • Customer support is also good for a licensed version, thereby saving the time, which in turn shows ROI as high.
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