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
NetBeans
Score 7.6 out of 10
N/A
NetBeans is a free and open source platform and integrated development environment (IDE).
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Pricing
Anaconda
NetBeans
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
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Offerings
Pricing Offerings
Anaconda
NetBeans
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Anaconda
NetBeans
Features
Anaconda
NetBeans
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.3
25 Ratings
10% above category average
NetBeans
-
Ratings
Connect to Multiple Data Sources
9.822 Ratings
00 Ratings
Extend Existing Data Sources
8.024 Ratings
00 Ratings
Automatic Data Format Detection
9.721 Ratings
00 Ratings
MDM Integration
9.614 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
8.5
25 Ratings
1% above category average
NetBeans
-
Ratings
Visualization
9.025 Ratings
00 Ratings
Interactive Data Analysis
8.024 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.0
26 Ratings
9% above category average
NetBeans
-
Ratings
Interactive Data Cleaning and Enrichment
8.823 Ratings
00 Ratings
Data Transformations
8.026 Ratings
00 Ratings
Data Encryption
9.719 Ratings
00 Ratings
Built-in Processors
9.620 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.2
24 Ratings
8% above category average
NetBeans
-
Ratings
Multiple Model Development Languages and Tools
9.023 Ratings
00 Ratings
Automated Machine Learning
8.921 Ratings
00 Ratings
Single platform for multiple model development
10.024 Ratings
00 Ratings
Self-Service Model Delivery
9.019 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
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.
NetBeans is extremely user friendly and easy to start developing complex applications. Adding and configuring external libraries is much simpler than in Eclipse. It is highly cost effective and most of the latest framework based libraries required are automatically downloaded to the projects. The overall tool is also light weight and consumes less memory as compared to other competitor tools.
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.
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.
NetBeans [should] work smoothly with systems having less RAM. Systems with less RAM face trouble with NetBeans.
File open history also requires improvement. Once NetBeans is restarted, all files are closed automatically and there is no shortcut to open last opened files.
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.
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.
Netbeans enhances my coding work, shows me where I have errors and helps find variable instances. I would be lost without find/replace in projects functionality as I use projects as templates for new projects. Occasionally the code hints aggravate me, but I understand that it is actually making me a better coder, working to get the 'green light' of a clean file with no errors or clumsy code.
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.
NetBeans has a very strong user community. We can find solutions here for almost all the problems we face. In addition, we can forward NetBeans Support teams the problems we cannot solve. We can get quick feedback from the support teams, but I generally try to solve my problems by following the forums.
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!
It works very smoothly as compared to other tools . The problem of restarting and reimporting the projects is not in the netbeans IDE . The front end development features are good . Netbeans connector is one of the best thing which enables us to deeply integrate netbeans IDE with google chrome browser
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.
By working on Netbeans I just learned one more tool and can teach others about it. One should learn every tool so that it might help someday if another editor is not available and you have to use different software for your work.
Compiling code became easy as it is not a feature of normal text editors. Only IDE can do this.