TensorFlow

TensorFlow TFX

Composite Score

8.1 /10

CX Score

8.3 /10

22 Reviews Write a Review

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What is TensorFlow TFX?

TFX is an end-to-end platform for deploying production ML pipelines. A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually. When you're ready to move your models from research to production, TFX can be used to create and manage a production pipeline.

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Awards & Recognition

TensorFlow TFX won the following awards in the Machine Learning Platforms category

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2024 Emotional Footprint Champion

Latest Award, 2024

Strategy and Innovation
Service Experience
Product Impact
Conflict Resolution

Latest Award, 2024

2024 Data Quadrant Gold Medalist

2024

8 Top Rated Capabilities

10 Top Rated Features

2024

TensorFlow TFX Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on TensorFlow TFX.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

91 Likeliness to Recommend

1
Since last award

100 Plan to Renew

85 Satisfaction of Cost Relative to Value

2
Since last award

Product Experience

Negotiation and Contract

Conflict Resolution

Strategy & Innovation

Service Experience

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Emotional Footprint Overview

Product Experience:: 89%
Negotiation and Contract:: 92%
Conflict Resolution:: 92%
Strategy & Innovation:: 89%
Service Experience:: 96%

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+92 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love TensorFlow TFX?

0% Negative

5% Neutral

95% Positive

Pros

Continually Improving Product
Trustworthy
Efficient Service
Caring

Feature Ratings

Average 84

Feature Engineering

Model Monitoring and Management

Performance and Scalability

Data Labeling

Algorithm Diversity

Model Tuning

Ensembling

Data Pre-Processing

Model Training

Data Exploration and Visualization

Openness and Flexibility

Vendor Capability Ratings

Average 83

Quality of Features

Breadth of Features

Ease of Customization

Business Value Created

Availability and Quality of Training

Ease of Implementation

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Ease of Data Integration

Vendor Support

TensorFlow TFX Reviews

Kyle W.

Role: Information Technology
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Feb 2025

A great Product For model Training and execution.

Likeliness to Recommend

8 /10

What differentiates TensorFlow TFX from other similar products?

I havent explored other products

What is your favorite aspect of this product?

The Playground. A quick way to test a model and visualise.

What do you dislike most about this product?

It can be complicated with all the features, but that is limited to my ML Experience.

What recommendations would you give to someone considering this product?

Play around in the sandbox to get the hand of it.

Pros

Helps Innovate
Reliable
Performance Enhancing
Enables Productivity

HARSHIL R.

Role: Information Technology
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jan 2025

Easy to use

Likeliness to Recommend

10 /10

What differentiates TensorFlow TFX from other similar products?

TensorFlow TFX stands out with its end-to-end machine learning platform, integrating data preparation, model training, validation, and deployment, providing a unified and scalable workflow for production-ready ML pipelines.

What is your favorite aspect of this product?

The seamless integration of various machine learning stages, from data preparation to deployment, which streamlines the development process and enables efficient, scalable, and production-ready ML pipelines.

What do you dislike most about this product?

The complexity and steep learning curve, particularly for users without extensive experience in machine learning, data engineering, or TensorFlow, which can make it challenging to fully leverage the product's capabilities.

What recommendations would you give to someone considering this product?

Carefully evaluate your team's expertise and needs, invest time in learning TensorFlow and TFX, and start with small-scale projects to ensure successful adoption and effective utilization of the product's capabilities.

Pros

Continually Improving Product
Performance Enhancing
Trustworthy
Inspires Innovation

Cons

Less Effective Service
Wastes Time
Inhibits Innovation

Jefferson A.

Role: Industry Specific Role
Industry: Engineering
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Jan 2025

"Powerful tool!"

Likeliness to Recommend

10 /10

What differentiates TensorFlow TFX from other similar products?

TensorFlow TFX differentiates itself with its end-to-end ML pipeline automation, seamless integration with TensorFlow, and production-ready tools like model validation, monitoring, and versioning. Its scalability supports distributed training and deployment across cloud and on-prem environments, while built-in components streamline workflows. Unlike many frameworks, TFX is designed specifically for moving machine learning from experimentation to reliable, scalable production systems.

What is your favorite aspect of this product?

For me its Scalability – TensorFlow TFX excels in handling large-scale machine learning workflows, allowing seamless model training, deployment, and monitoring in production environments. Its ability to scale efficiently across distributed systems is a key strength.

What do you dislike most about this product?

For me its the steep learning curve – While powerful, TensorFlow TFX can be difficult for newcomers to navigate due to its complexity and the need for familiarity with TensorFlow's ecosystem, which can slow down initial adoption.

What recommendations would you give to someone considering this product?

Master TensorFlow first – Familiarity with TensorFlow is essential for leveraging TFX effectively. Prepare for a learning curve – Be ready to invest time in understanding TFX's components and pipeline setup. Leverage community support – Use the extensive documentation and forums to troubleshoot and optimize workflows.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

TensorFlow TFX

What is TensorFlow TFX?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

2024 Data Quadrant Gold Medalist

TensorFlow TFX Ratings

91 Likeliness to Recommend

1 Since last award

100 Plan to Renew

85 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

Emotional Footprint Overview

+92 Net Emotional Footprint

How much do users love TensorFlow TFX?

Chart

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Feature Engineering Ability to extract and build features from raw data.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Data Labeling Ability to annotate/ label data to create a training data set.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Model Tuning 'Ability to fine-tune models based on monitoring feedback within the platform.

Ensembling 'Ability to combine ML models for best results.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Model Training Ability to train a model with a range of data sets that you provide.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

TensorFlow TFX Reviews

Kyle W.

A great Product For model Training and execution.

Likeliness to Recommend

Pros

HARSHIL R.

Easy to use

Likeliness to Recommend

Pros

Cons

Jefferson A.

"Powerful tool!"

Likeliness to Recommend

Pros

Most Popular TensorFlow TFX Comparisons

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1
Since last award

2
Since last award

Feature Ratings

Feature Engineering

Model Monitoring and Management

Performance and Scalability

Data Labeling

Algorithm Diversity

Model Tuning

Ensembling

Data Pre-Processing

Model Training

Data Exploration and Visualization

Openness and Flexibility

Vendor Capability Ratings

Quality of Features

Breadth of Features

Ease of Customization

Business Value Created

Availability and Quality of Training

Ease of Implementation

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Ease of Data Integration

Vendor Support