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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

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Retail Analytics

Score 7.9

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Databricks Data Intelligence Platform Reviews

Karthika S.

Role: Information Technology
Industry: Finance
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Sep 2024

Easy to implement and very stable data platform

Likeliness to Recommend

2 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Databricks platform is offering small to mid level organizations like my organization with stable cloud based data platform. It is very easy to setup a python/scala based data ingestion platforms streaming live data in realtime for various input events. Lakehouse features are great in capturing and processing the Changed delta along into gold, silver layers. Compared with other products in the market, this is a solid platform which is reliable and predictable environment without unexcepted environment errors.

What is your favorite aspect of this product?

Unity catalog feature provided by databricks is really great tool for showing the lineage information across various tables data flow, adding description and tag information and easy to use access control. Lakehouse features in databricks is really great.

What do you dislike most about this product?

There is a little increased cost compared with hosting bigdata applications directly in AWS. But the features offered and time saved for developers and analysts is worth the cost for the management for small organizations.

What recommendations would you give to someone considering this product?

Databricks is a great platform which you can build on top of the cloud platform of our choice. The workspace works seamlessly and is very reliable for production grade applications. They do regular updates for features and enhance security and other features. So you can definitely try this product.

Pros

Continually Improving Product
Reliable
Enables Productivity
Unique Features

Cons

Under Delivered

Alenandro S.

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

Validated Review

Verified Reviewer

Submitted Apr 2024

To organize and analyze data.

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

The Apache Spark distributed processing engine, providing excellent performance and scalability to handle massive volumes of data, is the foundation on which Databricks is built. Using Spark makes it simple with Databricks, allowing you to fully utilize its potential without having to deal with its underlying complexity.

What is your favorite aspect of this product?

Because it combines technologies for artificial intelligence, machine learning, data processing, and analysis, I appreciate Databricks Data Intelligence Platform. This enables groups to collaborate within a single environment on data projects from ingestion to production.

What do you dislike most about this product?

The complexity of data projects and the growth of clusters can make managing and maintaining Databricks infrastructure more difficult and call for specific knowledge of systems administration and performance optimization.

What recommendations would you give to someone considering this product?

I suggest... Elastic scaling based on user requirements is built into Databricks. It can manage any size data set—from tiny to petabytes—and adapt its computing power automatically to demand.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Gourav J.

Role: Information Technology
Industry: Technology
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Apr 2024

Easy to use, but a bit pricey.

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Easy, fast, cost efficinet

What is your favorite aspect of this product?

unity catalogue and workflows

What do you dislike most about this product?

nothing as of now

What recommendations would you give to someone considering this product?

more interaction with data engineers

Pros

Helps Innovate
Caring
Over Delivered
Continually Improving Product

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

Karthika S.

Easy to implement and very stable data platform

Likeliness to Recommend

Pros

Cons

Alenandro S.

To organize and analyze data.

Likeliness to Recommend

Pros

Gourav J.

Easy to use, but a bit pricey.

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