Anaconda vs. Labelbox

Anaconda

Labelbox

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Anaconda	Score 8.7 out of 10	N/A	Anaconda 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
Labelbox	Score 0.0 out of 10	N/A	Labelbox aims to solve the problem of taking artificial intelligence and machine learning initiatives from research and development into production. In addition to working directly with their customers, Labelbox's main product is a platform designed to make it easy to create and manage labeled data, enabling rapid deployment of artificial intelligence applications.	$6 Per Hour

Pricing

Anaconda

Labelbox

Editions & Modules

Free Tier: $0
per month
Starter Tier: $15
per month per user
Business: $50
per month per user
Custom: Contact Sales

Workforce Services: $6.00
Per Hour

Offerings

Pricing Offerings
Anaconda	Labelbox
Free Trial
No	No
Free/Freemium Version
Yes	No
Premium Consulting/Integration Services
No	No

Entry-level Setup Fee

No setup fee

Additional Details

Users within organizations with 200+ employees/contractors (including Affiliates) require a paid Business license. Academic and non-profit research institutions may qualify for exemptions.

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More Pricing Information

Community Pulse
	Anaconda	Labelbox
Considered Both Products	Anaconda RS Ranu Singh Technology Manager 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 Helpful? Ammar Aboalrub Freelancer 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 Helpful? Verified User Anonymous 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 Helpful? Zayed Rais Program Analyst 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 Helpful? Jay Thakkar Student 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 Helpful? RV Rounak Verma Data Analyst 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 Helpful? Gabriel Krahn Analista de Suporte de Sistemas 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 Helpful? Verified User Anonymous Chose Anaconda This is an open source tool and used very easily. All the notebooks are under one navigator solved the whole problem. Incentivized Helpful? AC Anomita Chandra Business Analyst 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 Helpful? Verified User Anonymous Chose Anaconda Free ware, better design ease of use Incentivized Helpful? Dilip Jain Senior Database Administrator 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 Helpful? Fernanda Ministerio Specialist 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 Helpful? Verified User Anonymous 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 Helpful? Verified User Anonymous 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 Helpful? Tigran Petrosyan Risk Management Specialist 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 Helpful? Juande Santander-Vela Software Development Lead / Product Manager at Solution Level Chose Anaconda Anaconda has 64-bit support in the community edition, and package management is more in line with the way we think. Incentivized Helpful? Verified User Anonymous Chose Anaconda I have not used another program like Anaconda before. Incentivized Helpful? Ryan McGarry Vice President of Research, Neuroscientist 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 Helpful? Xiaotong Song Business Analyst 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 Helpful? Verified User Anonymous 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 Helpful? Verified User Anonymous Chose Anaconda I like SpyDER, which comes with Anaconda better for its intuitive layout and variable explorer options. Incentivized Helpful? Verified User Anonymous 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 Helpful? Verified User Anonymous Chose Anaconda Suitable for Python development where there’s internal supporting for Python; otherwise, other platform offers similar capabilities with lower cost. Incentivized Helpful? Matthew Deakyne Academic Services Manager 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 Helpful? Verified User Anonymous 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 Helpful?	Labelbox No answer on this topic

Features

Anaconda

Labelbox

Platform Connectivity

Comparison of Platform Connectivity features of Product A and Product B
	Anaconda 9.3 Ratings 11% above category average	Labelbox - Ratings
Connect to Multiple Data Sources	9.80 Ratings	00 Ratings
Extend Existing Data Sources	8.00 Ratings	00 Ratings
Automatic Data Format Detection	9.70 Ratings	00 Ratings
MDM Integration	9.60 Ratings	00 Ratings

Data Exploration

Comparison of Data Exploration features of Product A and Product B
	Anaconda 8.5 Ratings 1% above category average	Labelbox - Ratings
Visualization	9.00 Ratings	00 Ratings
Interactive Data Analysis	8.00 Ratings	00 Ratings

Data Preparation

Comparison of Data Preparation features of Product A and Product B
	Anaconda 9.0 Ratings 10% above category average	Labelbox - Ratings
Interactive Data Cleaning and Enrichment	8.80 Ratings	00 Ratings
Data Transformations	8.00 Ratings	00 Ratings
Data Encryption	9.70 Ratings	00 Ratings
Built-in Processors	9.60 Ratings	00 Ratings

Platform Data Modeling

Comparison of Platform Data Modeling features of Product A and Product B
	Anaconda 9.2 Ratings 9% above category average	Labelbox - Ratings
Multiple Model Development Languages and Tools	9.00 Ratings	00 Ratings
Automated Machine Learning	8.90 Ratings	00 Ratings
Single platform for multiple model development	10.00 Ratings	00 Ratings
Self-Service Model Delivery	9.00 Ratings	00 Ratings

Model Deployment

Comparison of Model Deployment features of Product A and Product B
	Anaconda 9.5 Ratings 11% above category average	Labelbox - Ratings
Flexible Model Publishing Options	10.00 Ratings	00 Ratings
Security, Governance, and Cost Controls	9.00 Ratings	00 Ratings

Best Alternatives
	Anaconda	Labelbox
Small Businesses	Jupyter Notebook Score 8.6 out of 10	InterSystems IRIS Score 8.1 out of 10
Medium-sized Companies	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
Enterprises	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
All Alternatives	View all alternatives	View all alternatives

User Ratings
	Anaconda	Labelbox
Likelihood to Recommend	10.0 (0 ratings)	- (0 ratings)
Likelihood to Renew	7.0 (0 ratings)	- (0 ratings)
Usability	9.0 (0 ratings)	- (0 ratings)
Support Rating	8.9 (0 ratings)	- (0 ratings)

User Testimonials
	Anaconda	Labelbox
Likelihood to Recommend	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 RS Ranu Singh Technology Manager Read full review	No answers on this topic
Pros	Installing packages is very easy with Anaconda. Anaconda comes with 'anaconda navigator', a terminal-like utility from which you can easily install R packages and python libraries. Launching R and python IDEs as well as Jupyter notebooks from anaconda navigator is simple, and Anaconda makes it very easy to keep these packages up-to-date. I really like the fact that if you don't want to install the full version of Anaconda, you can opt to install a lightweight version (called Miniconda) that includes less python libraries and only core conda. I've installed it when I didn't want to take up as much disk space as Anaconda requires, but it works just the same. Incentivized Maike Holthuijzen Ph.D student Read full review	No answers on this topic
Cons	More graphics need in Spyder book. If you work for couple of years then you will be bored with the graphics. Extra tools are required for making it secure. We uses extra tools for adding Username /Password to Jupyter. R Studio Hangs a lot when open from Anaconda Navigator. Incentivized Verified User Anonymous Read full review	No answers on this topic
Likelihood to Renew	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 Matthew Deakyne Academic Services Manager Read full review	No answers on this topic
Usability	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 RS Ranu Singh Technology Manager Read full review	No answers on this topic
Support Rating	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 Ryan McGarry Vice President of Research, Neuroscientist Read full review	No answers on this topic
Alternatives Considered	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. Incentivized RV Rounak Verma Data Analyst Read full review	No answers on this topic
Return on Investment	Positive impact - Multiple options for data presenting , visualizing and sharing. (Eg: R-Markdown). Positive impact - Ease of access to build complex machine learning models. (I work in NLP, it has multiple built in models to analyze the various contexts). Positive impact - Conda package let's to deal with external packages which can be used in Jupyter. Incentivized AC Anomita Chandra Business Analyst Read full review	No answers on this topic
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