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Databricks

Databricks Data Intelligence Platform

Composite Score

8.7 /10

CX Score

9.1 /10

61 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 Emotional Footprint Champion

Latest Award, 2025

Strategy and Innovation
Contract Negotiation
Conflict Resolution

Latest Award, 2025

2025 Data Quadrant Champion

2025

4 Top Rated Capabilities

4 Top Rated Features

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.

87 Likeliness to Recommend

95 Plan to Renew

5
Since last award

78 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.

+96 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

5% Neutral

95% Positive

Pros

Continually Improving Product
Fair
Friendly Negotiation
Helps Innovate

Feature Ratings

Average 81

Performance and Scalability

Model Training

Feature Engineering

Data Pre-Processing

Openness and Flexibility

Algorithm Diversity

Data Ingestion

Model Tuning

Pre-Packaged AI/ML Services

Ensembling

Algorithm Recommendation

Vendor Capability Ratings

Average 80

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Data Integration

Availability and Quality of Training

Quality of Features

Ease of Implementation

Usability and Intuitiveness

Business Value Created

Ease of Customization

Vendor Support

Ease of IT Administration

Also Featured in...

Data Preparation for Analytics

Score 8.8

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Analytical Data Store

Score 8.1

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

Retail Analytics

Score 7.9

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Databricks Data Intelligence Platform Reviews

Nicky R.

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

Validated Review

Verified Reviewer

Submitted Dec 2024

Leading data intelligence platform, for me

Likeliness to Recommend

8 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Obviously, this should be its Apache spark processing engine. It is the major reason why we have been able to utilize Databricks to smoothly manage and process all data formats and types on a large scale. Its support for multiple data frameworks and languages is another area of differential, I think.

What is your favorite aspect of this product?

Its ability to unify a variety of workflows . This makes it easier for the different type of data professionals in my organization to collaborate and work together. Thereby increasing the speed and efficiency with which we can generate insights from large scale data pipelines.

What do you dislike most about this product?

There is a high chance for small sized teams to find Databricks expensive. Databricks pricing model is not favourable to small sized teams.

What recommendations would you give to someone considering this product?

For large scale data management, I think Databricks is a platform to try..

Pros

Reliable
Performance Enhancing
Enables Productivity
Unique Features

Tejasree G.

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

Validated Review

Verified Reviewer

Submitted Nov 2024

This is an outstanding product.

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Databricks platform offers a collaborative workspace for data engineers and scientists, unlike many other products focusing on just one part of the data lifecycle.

What is your favorite aspect of this product?

it integrates with multiple cloud providers like AWS, AZURE, GCP

What do you dislike most about this product?

For businesses operating on tight budgets, the pricing model may be higher compared to other solutions.

What recommendations would you give to someone considering this product?

I suggest enhancing collaborative notebooks to allow real-time teamwork on code and data visualization, facilitating easier collaboration for teams on intricate data projects.

Pros

Helps Innovate
Reliable
Performance Enhancing
Enables Productivity

M.D.Abdul R.

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

Validated Review

Verified Reviewer

Submitted Oct 2024

Great diversified product, easy to use but costly.

Likeliness to Recommend

10 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Data bricks leverages the different department works such as Data Analyst, Data engineering, Data Scientist and machine learning. A project requiring end to end work such as analysis of raw data from Data Analyst, Data cleansing and Preparation using Data engineering and finally forecasting using Data Science and Machine learning.

What is your favorite aspect of this product?

Data bricks can use Different languages such as pyspark, SQL and python using magic commands which makes the user to leverage different languages in the pipeline.

What do you dislike most about this product?

Due to the vast scope of data bricks for the project, Cost is comparatively high when compared to other technologies.

What recommendations would you give to someone considering this product?

Best product when project involving complex data ingestion and data processing.

Pros

Helps Innovate
Continually Improving Product
Trustworthy
Fair

Most Popular Databricks Data Intelligence Platform Comparisons

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Databricks Data Intelligence Platform

What is Databricks Data Intelligence Platform?

Company Details

Need Assistance?

Awards & Recognition

2025 Emotional Footprint Champion

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

87 Likeliness to Recommend

95 Plan to Renew

5 Since last award

78 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+96 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.

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

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

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

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, 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 Tuning Ability to fine-tune models based on monitoring feedback within the platform.

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

Ensembling 'Ability to combine ML models for best results.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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

Also Featured in...

Data Preparation for Analytics

Analytical Data Store

Retail Analytics

Databricks Data Intelligence Platform Reviews

Nicky R.

Leading data intelligence platform, for me

Likeliness to Recommend

Pros

Tejasree G.

This is an outstanding product.

Likeliness to Recommend

Pros

M.D.Abdul R.

Great diversified product, easy to use but costly.

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

5
Since last award

1
Since last award

Feature Ratings

Performance and Scalability

Model Training

Feature Engineering

Data Pre-Processing

Openness and Flexibility

Algorithm Diversity

Data Ingestion

Model Tuning

Pre-Packaged AI/ML Services

Ensembling

Algorithm Recommendation

Vendor Capability Ratings

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Data Integration

Availability and Quality of Training

Quality of Features

Ease of Implementation

Usability and Intuitiveness

Business Value Created

Ease of Customization

Vendor Support

Ease of IT Administration