Databricks

Databricks Data Intelligence Platform

Composite Score

8.6 /10

CX Score

9.0 /10

46 Reviews Write a Review

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What is Databricks Data Intelligence Platform?

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals.

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Awards & Recognition

Databricks Data Intelligence Platform won the following awards in the Machine Learning Platforms category

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2025 Data Quadrant Champion

Latest Award, 2025

4 Top Rated Capabilities

4 Top Rated Features

Latest Award, 2025

2024 Data Quadrant Champion

2024

3 Top Rated Capabilities

8 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2023

2023 Data Quadrant Champion

2023

3 Top Rated Capabilities

4 Top Rated Features

2023

2022 Emotional Footprint Champion

2022

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2022

2022 Data Quadrant Champion

2022

2 Top Rated Capabilities

2 Top Rated Features

2022

Databricks Data Intelligence Platform Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Databricks Data Intelligence Platform.

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.

88 Likeliness to Recommend

100 Plan to Renew

80 Satisfaction of Cost Relative to Value

1
Since last award

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Emotional Footprint Overview

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.

+97 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 Databricks Data Intelligence Platform?

0% Negative

4% Neutral

96% Positive

Pros

Continually Improving Product
Fair
Friendly Negotiation
Trustworthy

Feature Ratings

Average 83

Performance and Scalability

Pre-Packaged AI/ML Services

Algorithm Diversity

Data Ingestion

Model Training

Data Pre-Processing

Feature Engineering

Ensembling

Model Monitoring and Management

Openness and Flexibility

Algorithm Recommendation

Vendor Capability Ratings

Average 81

Ease of Data Integration

Product Strategy and Rate of Improvement

Quality of Features

Availability and Quality of Training

Usability and Intuitiveness

Breadth of Features

Ease of Implementation

Business Value Created

Ease of Customization

Ease of IT Administration

Vendor Support

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Data Preparation for Analytics

Score 8.7

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Retail Analytics

Score 8.0

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Databricks Data Intelligence Platform Reviews

Cathey M.

Role: Industry Specific Role
Industry: Other
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jun 2022

It is an excellent solution for data science.

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

The straightforward of use is that the most useful feature I like concerning MLFlow, it can use locally with none need for preparation on any server, nice UI that permits use to go looking through general experiments and flexibility of adjusting information stores. Simple administration, easy to make jobs from notebooks, great development environment, new and exciting options coming.

What is your favorite aspect of this product?

MLFlow has been instrumental in providing a decoupled interface between coaching and prediction part of our ml pipelines where we are able to store model information as part of training cycle and so in prediction we are able to leverage and decide model with highest roc or simply latest by chronological sorting and overall just help job in pursuit our experiments. It’ terribly helpful once it involves tracking performance of machine learning models. Acts like a dashboard that will otherwise ought to be built from scratch.

What do you dislike most about this product?

Generally slow to render in databricks environment as UI however that would be related to our databricks setup. There aren’t any major downsides but the model coaching part according to me is still higher run locally for comfy experiments. The UI style is in Django I believe which is a bit laggy and slow improvement will be done on that side.

What recommendations would you give to someone considering this product?

Mlflow tracking has been a significant advantage for maintaining the record of the results of the experiments we carry out on the information using different parameters. Tracking the results and parameters is extremely useful for achieving the foremost optimized solution. Attributable to these wonderful options I like to recommend this software.

Pros

Continually Improving Product
Performance Enhancing
Trustworthy
Efficient Service

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

Validated Review

Anonymous Reviewer

Submitted May 2022

Costly but effective

Likeliness to Recommend

8 /10

Pros

Helps Innovate
Reliable
Performance Enhancing
Security Protects

Cons

Less Efficient Service
Wastes Time

Pablo S.

Role: Information Technology
Industry: Food and Beverage
Involvement: Vendor Selection and Purchasing

Validated Review

Verified Reviewer

Submitted May 2022

Best tool ever!

Likeliness to Recommend

10 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Features. Delta tables, live tables mlflow

What is your favorite aspect of this product?

Delta format

What do you dislike most about this product?

Do not have servless

What recommendations would you give to someone considering this product?

Use it!

Pros

Helps Innovate
Efficient Service
Caring
Fair

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Databricks Data Intelligence Platform

What is Databricks Data Intelligence Platform?

Company Details

Need Assistance?

Awards & Recognition

2025 Data Quadrant Champion

2024 Data Quadrant Champion

2023 Emotional Footprint Champion

2023 Data Quadrant Champion

2022 Emotional Footprint Champion

2022 Data Quadrant Champion

Databricks Data Intelligence Platform Ratings

88 Likeliness to Recommend

100 Plan to Renew

80 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+97 Net Emotional Footprint

How much do users love Databricks Data Intelligence Platform?

Pros

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

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

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

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

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

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

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

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

Ensembling 'Ability to combine ML models for best results.

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

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

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

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

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

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.

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.

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.

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.

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 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.

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.

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.

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

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.

Also Featured in...

Data Preparation for Analytics

Retail Analytics

Databricks Data Intelligence Platform Reviews

Cathey M.

It is an excellent solution for data science.

Likeliness to Recommend

Pros

Costly but effective

Likeliness to Recommend

Pros

Cons

Pablo S.

Best tool ever!

Likeliness to Recommend

Pros

Most Popular Databricks Data Intelligence Platform Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

AWS Machine Learning

Microsoft Azure Machine Learning

DataRobot AI Platform

Alteryx

1
Since last award

Feature Ratings

Performance and Scalability

Pre-Packaged AI/ML Services

Algorithm Diversity

Data Ingestion

Model Training

Data Pre-Processing

Feature Engineering

Ensembling

Model Monitoring and Management

Openness and Flexibility

Algorithm Recommendation

Vendor Capability Ratings

Ease of Data Integration

Product Strategy and Rate of Improvement

Quality of Features

Availability and Quality of Training

Usability and Intuitiveness

Breadth of Features

Ease of Implementation

Business Value Created

Ease of Customization

Ease of IT Administration

Vendor Support