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Databricks

Databricks Data Intelligence Platform

Composite Score

8.6 /10

CX Score

9.0 /10

48 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.

Company Details

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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

Service Experience
Product Impact
Contract Negotiation

2024

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
Reliable

Feature Ratings

Average 83

Performance and Scalability

Pre-Packaged AI/ML Services

Algorithm Diversity

Data Ingestion

Model Training

Data Pre-Processing

Feature Engineering

Algorithm Recommendation

Ensembling

Openness and Flexibility

Model Monitoring and Management

Vendor Capability Ratings

Average 82

Ease of Data Integration

Product Strategy and Rate of Improvement

Quality of Features

Availability and Quality of Training

Breadth of Features

Usability and Intuitiveness

Ease of Implementation

Business Value Created

Ease of Customization

Ease of IT Administration

Vendor Support

Also Featured in...

Data Preparation for Analytics

Score 8.7

View Databricks Data Intelligence Platform in this category (opens in a new tab)

Retail Analytics

Score 8.0

View Databricks Data Intelligence Platform in this category (opens in a new tab)

Analytical Data Store

Score 7.9

View Databricks Data Intelligence Platform in this category (opens in a new tab)

Databricks Data Intelligence Platform Reviews

Role: Consultant
Industry: Retail
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Easy to use User friendly Lots of features

Likeliness to Recommend

9 /10

Pros

Reliable
Enables Productivity
Efficient Service
Respectful

Sanjay B.

Role: C-Level
Industry: Technology
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Apr 2022

Scalable and Easy to spin

Likeliness to Recommend

10 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Leverages Apache Spark which is designed for heavy lifting workloads. Highly optimized Spark clusters in Databricks have a great advantage over Cloud Datawarehouses such as Snowflake or BigQuery.

What is your favorite aspect of this product?

Its available on 3 major cloud vendors.

What do you dislike most about this product?

Its more close tied to Azure cloud than other cloud vendors.

What recommendations would you give to someone considering this product?

They can include low code/no code features to write spark programs.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Naresh S.

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

Validated Review

Verified Reviewer

Submitted Apr 2022

Fantastic product with easy integration

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Easy administration, smooth integration with other products and easy scale up/down

What is your favorite aspect of this product?

Smooth release of new features, easy integration and less of troubleshooting

What do you dislike most about this product?

Some documentation is not up to date. For example external metastore o sql server. As per documentation it supports only 1.2.1 version but actually it works fine on 2.3.0

What recommendations would you give to someone considering this product?

Go for it and use it for big data

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

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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.

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

Ensembling 'Ability to combine ML models for best results.

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

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

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.

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.

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 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

Analytical Data Store

Databricks Data Intelligence Platform Reviews

Easy to use User friendly Lots of features

Likeliness to Recommend

Pros

Sanjay B.

Scalable and Easy to spin

Likeliness to Recommend

Pros

Naresh S.

Fantastic product with easy integration

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

Algorithm Recommendation

Ensembling

Openness and Flexibility

Model Monitoring and Management

Vendor Capability Ratings

Ease of Data Integration

Product Strategy and Rate of Improvement

Quality of Features

Availability and Quality of Training

Breadth of Features

Usability and Intuitiveness

Ease of Implementation

Business Value Created

Ease of Customization

Ease of IT Administration

Vendor Support