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.

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

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

Also Featured in...

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

Bir B.

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

Validated Review

Verified Reviewer

Submitted Apr 2024

Worth the money, makes development efficient

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Databricks DIP is great 'cause: It stores all kinds of data easily with its Lakehouse setup. It works with lots of tools and doesn't tie you down to one. It's all about Machine Learning, making data, ML, and insights in one place. You can pick which cloud you want to use. It can handle a ton of data without breaking a sweat.

What is your favorite aspect of this product?

It's all about Machine Learning, making data, ML, and insights in one place.

What do you dislike most about this product?

Nothing as of now.

What recommendations would you give to someone considering this product?

Learning curve might be steep, but its really efficient.

Pros

Effective Service
Caring
Saves Time
Respectful

Sehaj K.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Ease for user

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Databricks Lakehouse Platform distinguishes itself through its unified approach to data management, combining the scalability and flexibility of data lakes with the reliability and performance of data warehouses. It offers seamless integration with popular data sources and tools, advanced analytics capabilities, and built-in machine learning frameworks, empowering organizations to derive insights from their data efficiently and effectively.

What is your favorite aspect of this product?

one notable aspect of Databricks Lakehouse Platform is its ability to unify data engineering, data science, and analytics workflows on a single platform, facilitating collaboration and accelerating time-to-insight for organizations.

What do you dislike most about this product?

I dont have any dislike

Pros

Helps Innovate
Enables Productivity
Trustworthy
Unique Features

Maryam A.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

For processing data streams

Likeliness to Recommend

9 /10

What differentiates Databricks Data Intelligence Platform from other similar products?

Advanced security and compliance capabilities are available with Databricks Lakehouse Platform. These features include data encryption to safeguard data integrity and confidentiality, data auditing, and integration with identity and access management systems.

What is your favorite aspect of this product?

Because of its close interaction with cloud providers like Azure, AWS, and Google Cloud Platform, Databricks Lakehouse Platform is well-liked for its ease of deployment and management in public cloud environments.

What do you dislike most about this product?

While lakehouse design can help with data unification and analytical capacities, it can also add to the complexity of data management and ETL process deployment.

What recommendations would you give to someone considering this product?

I recommend using Databricks Lakehouse Platform, it has features and capabilities to manage, store and analyze data effectively and scalably.

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.

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

Bir B.

Worth the money, makes development efficient

Likeliness to Recommend

Pros

Sehaj K.

Ease for user

Likeliness to Recommend

Pros

Maryam A.

For processing data streams

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