Azure Databricks
Reviews
Star rating
Rank in Big Data Analytics
Pros and cons
Pros
- Ease of Use
- Features
- Integrations
- Speed
- Scaling
- Analytics
Cons
- Learning Curve
- Slow Performance
- Difficult Setup
- Workflow Issues
- Complexity
- Unclear Pricing
Traffic & LLM citations
Source: G2 review data
Winning from
Losing to
Key stats
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 25.1% |
| Mid-Market | 27.6% |
| Enterprise | 47.3% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2024 Q4 | 3 | 4.7 |
| 2025 Q1 | 1 | 5.0 |
| 2025 Q2 | 2 | 5.0 |
| 2025 Q3 | 4 | 4.6 |
| 2025 Q4 | 5 | 4.3 |
| 2026 Q1 | 5 | 4.7 |
| 2026 Q2 | 7 | 4.7 |
| 2026 Q3 | 1 | 5.0 |
Satisfaction ratings
What reviewers say
Powerful Platform for Modern Data Engineering
“I like Azure Databricks because it makes working with large datasets much easier and more organized. I mainly use PySpark notebooks for data processing, transformations, and automation. The integration with Azure Data Factory and Azure storage is especially useful for building en”
All-in-One Data Platform with an Intuitive, User-Friendly Interface
“It makes data easy and simple to understand even if we are not from technical background, i dont need to swap or switch different app or software now for data eng , analytics or data science all can be done in once now. The interface is very good and user friendly easy to underst”
Azure Databricks: Scalable, Fast Collaboration with Seamless Azure Integration
“What I like best about Azure Databricks is how well it combines scalability, speed, and collaboration in a single environment. It makes it easy to work with large datasets, build and run data pipelines efficiently, and support both engineering and analytics tasks without switchin”