Skip to main content
TrustRadius
Anaconda

Anaconda

Overview

What is Anaconda?

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.…

Read more
Recent Reviews

TrustRadius Insights

Anaconda is a versatile tool that has found widespread use across various departments and teams within organizations. It is highly …
Continue reading
Read all reviews

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Data Transformations (25)
    9.6
    96%
  • Visualization (24)
    9.6
    96%
  • Extend Existing Data Sources (23)
    8.9
    89%
  • Interactive Data Analysis (23)
    8.9
    89%
Return to navigation

Pricing

View all pricing

Free Tier

$0

Cloud
per month

Starter Tier

$9

Cloud
per month

Business Tier

$50

Cloud
per month per user

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visitwww.anaconda.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
Return to navigation

Product Demos

Introducing Anaconda Distribution for Python in Excel

YouTube

Introducing: Anaconda Assistant

YouTube

Anaconda for Open-Source Security with Python and R

YouTube

AI Development in the Enterprise with Anaconda's Data Science Platform

YouTube
Return to navigation

Features

Platform Connectivity

Ability to connect to a wide variety of data sources

9.5
Avg 8.5

Data Exploration

Ability to explore data and develop insights

9.2
Avg 8.4

Data Preparation

Ability to prepare data for analysis

9.4
Avg 8.2

Platform Data Modeling

Building predictive data models

9.3
Avg 8.5

Model Deployment

Tools for deploying models into production

9.6
Avg 8.6
Return to navigation

Product Details

What is Anaconda?

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.


Anaconda Features

Platform Connectivity Features

  • Supported: Extend Existing Data Sources

Data Exploration Features

  • Supported: Visualization
  • Supported: Interactive Data Analysis

Data Preparation Features

  • Supported: Data Transformations
  • Supported: Data Encryption

Platform Data Modeling Features

  • Supported: Multiple Model Development Languages and Tools
  • Supported: Automated Machine Learning
  • Supported: Single platform for multiple model development
  • Supported: Self-Service Model Delivery

Model Deployment Features

  • Supported: Flexible Model Publishing Options
  • Supported: Security, Governance, and Cost Controls

Anaconda Integrations

Anaconda Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo
Supported CountriesGlobal

Frequently Asked Questions

Dataiku, Domino Enterprise MLOps Platform, and Posit are common alternatives for Anaconda.

Reviewers rate Connect to Multiple Data Sources highest, with a score of 9.8.

The most common users of Anaconda are from Enterprises (1,001+ employees).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(142)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Anaconda is a versatile tool that has found widespread use across various departments and teams within organizations. It is highly regarded by users for its ability to import libraries, train predictive algorithms, and estimate value sources. This makes it an invaluable tool for data scientists and machine learning engineers who rely on it for real-world problem-solving and project development. Anaconda's package management system is particularly appreciated as it helps maintain up-to-date Python libraries, saving time and avoiding installation issues. Additionally, its cross-platform program facilitates seamless collaboration among Mac/PC/Linux users.

One of the key use cases of Anaconda is in the field of business intelligence and data science. Professionals in this domain utilize Anaconda for analysis, forecasting, and answering critical questions. Organizations also leverage Anaconda to identify the impact of COVID-19 on different products by analyzing customer survey data. The software's robust capabilities make it an ideal choice for managing large-scale projects with multiple dependencies, ensuring reproducibility of analysis, and providing a standardized working environment. Furthermore, Anaconda serves as a comprehensive data analysis environment, particularly when coupled with the user-friendly Jupyter Notebook.

In addition to its applications in data science and business intelligence, Anaconda finds utility in other areas such as banking departments for coding complex tasks like risk prediction and evaluation. It also supports software development objectives by enabling quick setup of development environments for employees. The product is widely used in analytics-based projects, including building small applications with Spyder and reporting and visualization with R and Orange. Moreover, researchers in fields like engineering and geoscience often turn to Anaconda as a research platform for prototyping custom algorithms and sharing progress with teammates.

Overall, Anaconda proves itself as an indispensable tool that streamlines coding workflows, ensures version control, enhances collaboration among teams, simplifies package management, enables efficient scripting in Python, offers a wide range of libraries and packages for various domains, automates routine tasks like excel sheet modifications, and provides a robust environment for data analysis and visualization.

Anaconda as a one-stop destination: Many users have found Anaconda to be a convenient and comprehensive solution for data science and programming tools. It has been praised by multiple reviewers for providing important tools such as Jupyter, Spyder, and R in one platform.

User-friendly interface: The simplicity and ease of use of Anaconda's user interface have been appreciated by many reviewers. They have found it intuitive and easy to navigate through files in Jupyter, as well as install new libraries.

Flexibility in working with Python environments: Users have highlighted the flexibility of Anaconda in working with multiple Python environments based on their requirements. This feature has been found useful for different use cases by several reviewers.

  1. Slow performance and high resource consumption: Several users have expressed frustration with the slow performance of Anaconda, particularly when it comes to bootstrapping the software and loading its contents. Additionally, some reviewers have mentioned that Anaconda can consume a significant amount of RAM, making it unsuitable for large projects or older machines.

  2. Difficulty in installing packages and libraries: Many users have encountered challenges when installing specific Python libraries using Anaconda's package manager, conda. Some reviewers had to uninstall and reinstall Anaconda multiple times to resolve issues with library installation. Others found it confusing to work with Anaconda alongside other Python packages and versions on their machine.

  3. Lack of support and technical troubleshooting difficulties: A number of users have mentioned the lack of support for the free version of Anaconda, making it difficult to troubleshoot issues without technical assistance. Reviewers felt frustrated when encountering software crashes while running code in Anaconda, leading to data loss. They also expressed dissatisfaction with the irregular security updates and the lack of integration with version control tools.

Users commonly recommend Anaconda as an excellent IDE tool for Python developers. They appreciate its user-friendly interface and the positive coding experience it provides. Users also find it easy to manage libraries in different programming languages. Additionally, they value the availability of helpful training materials and tutorials, particularly for beginners in data science and machine learning. As a result, users suggest starting with Anaconda for beginners and using it for projects involving Python programming. Furthermore, they recommend considering PyCharm as a more sophisticated IDE alternative.

Attribute Ratings

Reviews

(1-25 of 29)
Companies can't remove reviews or game the system. Here's why
Ammar Aboalrub | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Platform Connectivity (4)
97.5%
9.8
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
100%
10.0
MDM Integration
100%
10.0
Data Exploration (2)
95%
9.5
Visualization
100%
10.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
97.5%
9.8
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
95%
9.5
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
20%
2.0
Connect to Multiple Data Sources
N/A
N/A
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
N/A
N/A
MDM Integration
N/A
N/A
Data Exploration (2)
40%
4.0
Visualization
80%
8.0
Interactive Data Analysis
N/A
N/A
Data Preparation (4)
60%
6.0
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
N/A
N/A
Built-in Processors
80%
8.0
Platform Data Modeling (4)
67.5%
6.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
90%
9.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
90%
9.0
Zayed Rais | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
77.5%
7.8
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
70%
7.0
MDM Integration
70%
7.0
Data Exploration (2)
75%
7.5
Visualization
80%
8.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
75%
7.5
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
72.5%
7.3
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
70%
7.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (2)
80%
8.0
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Data Exploration (2)
80%
8.0
Visualization
80%
8.0
Interactive Data Analysis
80%
8.0
Data Preparation (2)
80%
8.0
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Platform Data Modeling (3)
80%
8.0
Multiple Model Development Languages and Tools
80%
8.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
80%
8.0
Jay Thakkar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
80%
8.0
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
80%
8.0
MDM Integration
70%
7.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
85%
8.5
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
80%
8.0
June 28, 2021

Anaconda Review

Dilip Jain | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
85%
8.5
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
N/A
N/A
Visualization
N/A
N/A
Interactive Data Analysis
N/A
N/A
Data Preparation (4)
60%
6.0
Interactive Data Cleaning and Enrichment
N/A
N/A
Data Transformations
90%
9.0
Data Encryption
70%
7.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
62.5%
6.3
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
N/A
N/A
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
70%
7.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
70%
7.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
90%
9.0
MDM Integration
N/A
N/A
Data Exploration (2)
75%
7.5
Visualization
70%
7.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
67.5%
6.8
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
N/A
N/A
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
95%
9.5
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
100%
10.0
Gabriel Krahn | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
70%
7.0
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
100%
10.0
MDM Integration
N/A
N/A
Data Exploration (2)
85%
8.5
Visualization
80%
8.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
37.5%
3.8
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
80%
8.0
Data Encryption
N/A
N/A
Built-in Processors
N/A
N/A
Platform Data Modeling (4)
N/A
N/A
Multiple Model Development Languages and Tools
N/A
N/A
Automated Machine Learning
N/A
N/A
Single platform for multiple model development
N/A
N/A
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
N/A
N/A
Flexible Model Publishing Options
N/A
N/A
Security, Governance, and Cost Controls
N/A
N/A
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
90%
9.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
70%
7.0
MDM Integration
100%
10.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
92.5%
9.3
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
60%
6.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
60%
6.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
50%
5.0
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
100%
10.0
MDM Integration
50%
5.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
100%
10.0
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
100%
10.0
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
80%
8.0
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
80%
8.0
MDM Integration
80%
8.0
Data Exploration (2)
70%
7.0
Visualization
70%
7.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
55%
5.5
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
80%
8.0
Data Encryption
N/A
N/A
Built-in Processors
70%
7.0
Platform Data Modeling (4)
67.5%
6.8
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
60%
6.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
70%
7.0
Model Deployment (2)
40%
4.0
Flexible Model Publishing Options
50%
5.0
Security, Governance, and Cost Controls
30%
3.0
Fernanda Ministerio | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
65%
6.5
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
N/A
N/A
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
95%
9.5
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
92.5%
9.3
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
72.5%
7.3
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
70%
7.0
Automatic Data Format Detection
70%
7.0
MDM Integration
70%
7.0
Data Exploration (2)
80%
8.0
Visualization
80%
8.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
70%
7.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
82.5%
8.3
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
75%
7.5
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
80%
8.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
80%
8.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
85%
8.5
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
90%
9.0
April 16, 2021

Review for Anaconda

Tigran Petrosyan | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
72.5%
7.3
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
90%
9.0
MDM Integration
N/A
N/A
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
72.5%
7.3
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
100%
10.0
Data Encryption
N/A
N/A
Built-in Processors
100%
10.0
Platform Data Modeling (4)
72.5%
7.3
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
50%
5.0
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
N/A
N/A
Automatic Data Format Detection
100%
10.0
MDM Integration
N/A
N/A
Data Exploration (2)
50%
5.0
Visualization
60%
6.0
Interactive Data Analysis
40%
4.0
Data Preparation (4)
75%
7.5
Interactive Data Cleaning and Enrichment
N/A
N/A
Data Transformations
100%
10.0
Data Encryption
100%
10.0
Built-in Processors
100%
10.0
Platform Data Modeling (4)
N/A
N/A
Multiple Model Development Languages and Tools
N/A
N/A
Automated Machine Learning
N/A
N/A
Single platform for multiple model development
N/A
N/A
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
N/A
N/A
Flexible Model Publishing Options
N/A
N/A
Security, Governance, and Cost Controls
N/A
N/A
Juande Santander-Vela | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
45%
4.5
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
N/A
N/A
MDM Integration
N/A
N/A
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
80%
8.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
65%
6.5
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
N/A
N/A
Flexible Model Publishing Options
N/A
N/A
Security, Governance, and Cost Controls
N/A
N/A
Ryan McGarry | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (3)
93.33333333333334%
9.3
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
100%
10.0
MDM Integration
80%
8.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
80%
8.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
50%
5.0
Built-in Processors
90%
9.0
Platform Data Modeling (3)
86.66666666666666%
8.7
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
90%
9.0
Model Deployment
N/A
N/A
Xiaotong Song | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
92.5%
9.3
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
90%
9.0
MDM Integration
100%
10.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
87.5%
8.8
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
87.5%
8.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
90%
9.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
90%
9.0
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
90%
9.0
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
80%
8.0
Visualization
70%
7.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
90%
9.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
92.5%
9.3
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
100%
10.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
100%
10.0
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity
N/A
N/A
Data Exploration (2)
75%
7.5
Visualization
70%
7.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
70%
7.0
Interactive Data Cleaning and Enrichment
70%
7.0
Data Transformations
80%
8.0
Data Encryption
60%
6.0
Built-in Processors
70%
7.0
Platform Data Modeling (3)
56.66666666666667%
5.7
Automated Machine Learning
40%
4.0
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
60%
6.0
Model Deployment (2)
45%
4.5
Flexible Model Publishing Options
50%
5.0
Security, Governance, and Cost Controls
40%
4.0
February 18, 2020

Anaconda for Python

Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
60%
6.0
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
80%
8.0
MDM Integration
N/A
N/A
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
45%
4.5
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
N/A
N/A
Built-in Processors
N/A
N/A
Platform Data Modeling (4)
67.5%
6.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
N/A
N/A
Flexible Model Publishing Options
N/A
N/A
Security, Governance, and Cost Controls
N/A
N/A
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
100%
10.0
Automatic Data Format Detection
80%
8.0
MDM Integration
80%
8.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
90%
9.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
92.5%
9.3
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
90%
9.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
90%
9.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
90%
9.0
Score 10 out of 10
Vetted Review
Verified User
Platform Connectivity (4)
80%
8.0
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
60%
6.0
Data Exploration (2)
80%
8.0
Visualization
90%
9.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
67.5%
6.8
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
90%
9.0
Data Encryption
50%
5.0
Built-in Processors
50%
5.0
Platform Data Modeling (4)
77.5%
7.8
Multiple Model Development Languages and Tools
90%
9.0
Automated Machine Learning
70%
7.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
70%
7.0
Model Deployment (1)
80%
8.0
Flexible Model Publishing Options
80%
8.0
Return to navigation