Anaconda vs. IBM ILOG CPLEX Optimization Studio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Anaconda
Score 8.6 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
IBM ILOG CPLEX Optimization Studio
Score 9.4 out of 10
N/A
IBM® ILOG® CPLEX® Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming.
$285
per month per user
Pricing
AnacondaIBM ILOG CPLEX Optimization Studio
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
No answers on this topic
Offerings
Pricing Offerings
AnacondaIBM ILOG CPLEX Optimization Studio
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
AnacondaIBM ILOG CPLEX Optimization Studio
Top Pros

No answers on this topic

Top Cons
Features
AnacondaIBM ILOG CPLEX Optimization Studio
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.3
25 Ratings
11% above category average
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
4% below category average
Connect to Multiple Data Sources9.822 Ratings9.02 Ratings
Extend Existing Data Sources8.024 Ratings7.02 Ratings
Automatic Data Format Detection9.721 Ratings8.02 Ratings
MDM Integration9.614 Ratings8.02 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
8.5
25 Ratings
0% above category average
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
17% above category average
Visualization9.025 Ratings10.02 Ratings
Interactive Data Analysis8.024 Ratings10.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.1
26 Ratings
11% above category average
IBM ILOG CPLEX Optimization Studio
7.3
2 Ratings
11% below category average
Interactive Data Cleaning and Enrichment8.823 Ratings5.01 Ratings
Data Transformations8.026 Ratings7.01 Ratings
Data Encryption9.719 Ratings8.02 Ratings
Built-in Processors9.620 Ratings9.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.2
24 Ratings
9% above category average
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
5% below category average
Multiple Model Development Languages and Tools9.023 Ratings10.02 Ratings
Automated Machine Learning8.921 Ratings5.01 Ratings
Single platform for multiple model development10.024 Ratings8.02 Ratings
Self-Service Model Delivery9.019 Ratings9.01 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Anaconda
9.5
21 Ratings
11% above category average
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
16% above category average
Flexible Model Publishing Options10.021 Ratings10.02 Ratings
Security, Governance, and Cost Controls9.020 Ratings10.02 Ratings
Best Alternatives
AnacondaIBM ILOG CPLEX Optimization Studio
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.0 out of 10
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Score 9.0 out of 10
Medium-sized Companies
Posit
Posit
Score 9.7 out of 10
Posit
Posit
Score 9.7 out of 10
Enterprises
Posit
Posit
Score 9.7 out of 10
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Score 9.7 out of 10
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User Ratings
AnacondaIBM ILOG CPLEX Optimization Studio
Likelihood to Recommend
10.0
(38 ratings)
9.0
(2 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
Usability
9.0
(3 ratings)
9.0
(1 ratings)
Support Rating
8.9
(9 ratings)
7.0
(1 ratings)
User Testimonials
AnacondaIBM ILOG CPLEX Optimization Studio
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.
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IBM
It is well suited for solving large-sized, mixed-integer, and integer programming problems. Now, the new version supports for Multi-Objective optimization along with some new algorithms such as Benders Decomposition. It is less appropriate for quadratic programming problems where the objective function is the product of multiple variables. However, it's very easy to code any problem.
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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.
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IBM
  • Linear Programming
  • Mixed-Integer Linear Programming
  • Non-Linear Convex-Optimization
  • Visualization
  • Shadow Price Analysis
  • Parameter Tuning
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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.
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IBM
  • Data handling from different sources like Note Pad, etc.
  • Large size of MILP problems.
  • Various parameters to set.
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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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IBM
No answers on this topic
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.
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IBM
It's nice to use and with good optimization.
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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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IBM
Honestly, to say, I never contacted CPLEX but used its forum to know/clarify any issues I faced.
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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!
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IBM
IBM CPLEX Optimization Studio covers wide range of problems in comparison to Gurobi and also offers a number of visualization tools for results analysis. It has better customization and parameter tuning options in comparison to Gurobi. It offers various API integrations such as Python, Java and C++ which is not the case with Gurobi.
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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.
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IBM
  • Faster computation leading to better internal customer relations
  • Able to solve high variable problems with ease
  • Anomaly detection became easier within business
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ScreenShots