Compare Apache Airflow and Databricks 
At a Glance
Market Segments
Mid-Market (45.0% of reviews)
Enterprise (44.2% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Apache Airflow
Star Rating
(125)4.4 out of 5
Market Segments
Mid-Market (45.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Apache AirflowDatabricks
Star Rating
(760)4.6 out of 5
Market Segments
Enterprise (44.2% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DatabricksSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Databricks excels in providing a comprehensive data workflow solution, with features like Genie and Lakehouse Connect that streamline data processing, analysis, and machine learning all in one platform. Users appreciate the notebook environment that simplifies their tasks.
- Users say Apache Airflow shines in its ability to create ETL pipelines, particularly highlighting its UI-driven DAG visualization. This feature makes understanding workflows and dependencies much easier, which is a significant advantage for teams managing complex data processes.
- Reviewers mention that Databricks offers superior support and ease of setup compared to Apache Airflow. Many users have noted the intuitive onboarding process, which helps teams get started quickly, while Airflow users have reported a steeper learning curve during initial setup.
- According to verified reviews, both platforms are praised for their flexibility, but Databricks stands out with its Unity Catalog, which enhances governance and access control across data assets. This feature has been a game-changer for enterprises migrating from traditional architectures.
- G2 reviewers highlight that while Apache Airflow is strong in managing workflows with clear task definitions and dependencies, it sometimes lacks the integrated features that Databricks provides, which can lead to users needing to switch between multiple tools for different tasks.
- Users report that Databricks has a higher overall satisfaction score, reflecting its robust capabilities and user-friendly design. In contrast, while Airflow is effective for specific use cases, some users feel it could benefit from more streamlined features to enhance day-to-day usability.
Pricing
Entry-Level Pricing
Apache Airflow
No pricing availableDatabricks
No pricing availableFree Trial
Apache Airflow
No trial information availableDatabricks
Free Trial is available
Ratings
Meets Requirements
9.0
92
9.0
596
Ease of Use
8.4
92
8.9
612
Ease of Setup
7.7
56
8.7
485
Ease of Admin
8.3
30
8.4
185
Quality of Support
8.2
84
8.7
573
Has the product been a good partner in doing business?
8.6
29
8.9
189
Product Direction (% positive)
9.5
86
9.6
583
Features by Category
Reports
Not enough data
8.5
14
Not enough data
7.9
12
Not enough data
8.6
13
Not enough data
8.2
10
Not enough data
9.0
17
Data Preparation
Not enough data
9.0
7
Not enough data
9.0
8
Data Modeling and Blending
Not enough data
9.1
9
Not enough data
9.0
8
Not enough data
8.9
9
Generative AI
Not enough data
9.2
10
Not enough data
9.3
7
Agentic AI - Analytics Platforms
Not enough data
9.4
8
Not enough data
8.9
6
Not enough data
8.6
7
Not enough data
8.6
7
Not enough data
8.5
8
Not enough data
9.3
7
Not enough data
9.4
6
Self Service
Not enough data
7.9
11
Not enough data
7.9
11
Not enough data
8.6
12
Not enough data
8.2
13
Not enough data
8.5
13
Not enough data
8.3
10
Deployment & Integration - Analytics Platforms
Not enough data
8.3
8
Not enough data
9.3
9
Not enough data
8.8
7
Not enough data
9.3
7
Advanced Analytics
Not enough data
8.6
13
Not enough data
8.5
13
Not enough data
9.2
15
Performance & Scalability - Analytics Platforms
Not enough data
9.0
8
Not enough data
9.7
5
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
9.1
9
Not enough data
8.7
9
Not enough data
8.8
7
Agentic AI Capabilities - Analytics Platforms
Not enough data
8.8
8
Not enough data
9.0
8
Not enough data
9.0
7
Not enough data
8.8
8
Personalized Intelligence - Analytics Platforms
Not enough data
9.3
7
Not enough data
8.1
9
Not enough data
8.5
8
Building Reports
Not enough data
9.0
160
Not enough data
8.7
151
Not enough data
7.7
127
Not enough data
8.4
151
Administration
Not enough data
8.8
100
Not enough data
8.6
94
Not enough data
9.0
95
Not enough data
8.7
99
Management
Not enough data
8.5
88
Not enough data
8.6
87
Not enough data
8.7
89
Not enough data
8.5
88
Not enough data
8.8
87
Compliance
Not enough data
8.9
100
Not enough data
8.7
93
Not enough data
8.9
95
Not enough data
8.7
96
Security
Not enough data
9.0
89
Not enough data
8.9
87
Not enough data
8.8
87
Data Quality
Not enough data
9.0
95
Not enough data
8.7
94
Not enough data
9.0
94
Maintainence
Not enough data
8.7
86
Not enough data
8.8
85
Generative AI
Not enough data
8.4
83
Not enough data
8.5
82
Agentic AI - Data Governance
Not enough data
8.6
11
Not enough data
8.9
12
Not enough data
9.1
15
Not enough data
8.6
13
Not enough data
9.1
13
Not enough data
9.0
14
Management
Not enough data
8.6
174
Not enough data
8.5
166
Functionality
Not enough data
9.1
178
Not enough data
9.2
180
Not enough data
9.1
175
Not enough data
9.0
169
Not enough data
9.2
171
Deployment
8.5
8
8.9
65
8.5
9
8.9
64
8.5
8
8.9
66
8.3
9
8.9
66
8.9
9
9.0
68
Deployment
8.5
9
8.9
62
8.8
8
8.8
62
8.5
8
8.6
66
8.3
9
8.9
65
9.4
8
9.0
66
Management
8.5
8
9.0
64
8.3
8
8.9
66
9.0
8
9.2
61
8.5
8
9.0
69
Operations
8.1
9
8.7
62
8.5
8
8.8
62
8.8
8
9.0
63
Management
8.8
8
8.8
61
8.5
8
8.7
61
8.8
8
9.1
59
Generative AI
7.7
8
8.3
28
7.9
8
8.3
28
System
Not enough data
8.9
181
Model Development
Not enough data
8.8
186
Not enough data
8.0
189
Not enough data
8.3
187
Not enough data
8.7
192
Model Development
Not enough data
8.5
173
Machine/Deep Learning Services
Not enough data
8.2
175
Not enough data
8.5
181
Not enough data
8.3
173
Not enough data
8.2
173
Machine/Deep Learning Services
Not enough data
8.4
159
Not enough data
8.4
161
Deployment
Not enough data
8.5
180
Not enough data
8.7
181
Not enough data
9.0
189
Generative AI
Not enough data
8.2
87
Not enough data
8.4
88
Not enough data
7.6
87
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
9.3
9
Not enough data
8.5
8
Not enough data
8.3
9
Not enough data
8.8
8
Not enough data
9.2
11
Not enough data
8.8
7
Not enough data
9.4
8
Data Management
Not enough data
9.1
187
|
Verified
Not enough data
8.9
182
|
Verified
Not enough data
8.9
183
|
Verified
Not enough data
8.8
182
|
Verified
Not enough data
8.7
169
|
Verified
Not enough data
9.1
174
|
Verified
Integration
Not enough data
8.8
170
|
Verified
Not enough data
8.8
169
|
Verified
Not enough data
9.1
178
|
Verified
Deployment
Not enough data
8.0
158
|
Verified
Not enough data
9.2
180
|
Verified
Performance
Not enough data
9.2
181
|
Verified
Security
Not enough data
8.9
172
|
Verified
Not enough data
8.9
170
|
Verified
Generative AI
Not enough data
8.5
78
Not enough data
8.4
77
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Maintenance
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Data Management
Not enough data
9.0
70
Not enough data
8.8
72
Not enough data
8.9
70
Not enough data
9.2
71
Agentic AI - DataOps Platforms
Not enough data
9.2
11
Not enough data
9.1
9
Not enough data
9.1
11
Not enough data
9.2
10
Not enough data
9.5
10
Analytics
Not enough data
8.9
69
Not enough data
8.6
69
Monitoring and Management
Not enough data
8.6
69
Not enough data
8.6
70
Cloud Deployment
Not enough data
9.0
65
Not enough data
9.0
66
Generative AI
Not enough data
9.0
38
Not enough data
8.9
38
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Customization - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Functionality - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data and Analytics - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Workflow Design & Integration - AI Orchestration
8.5
21
Not enough data
8.2
18
Not enough data
8.5
19
Not enough data
8.5
17
Not enough data
8.7
17
Not enough data
7.7
15
Not enough data
Performance Optimization & Analytics - AI Orchestration
8.2
18
Not enough data
7.7
15
Not enough data
8.6
15
Not enough data
7.0
15
Not enough data
8.1
15
Not enough data
8.5
17
Not enough data
Governance & Compliance Controls - AI Orchestration
7.7
14
Not enough data
7.3
14
Not enough data
8.1
15
Not enough data
8.1
16
Not enough data
8.3
15
Not enough data
Traffic Management & Performance - AI Gateways
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Governance & Observability - AI Gateways
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Database
Not enough data
8.7
238
Not enough data
8.9
246
Not enough data
9.3
266
Integrations
Not enough data
8.3
219
Not enough data
9.1
269
Platform
Not enough data
8.9
263
Not enough data
8.9
254
Not enough data
9.1
269
Processing
Not enough data
9.1
248
Not enough data
9.0
255
Data Transformation
Not enough data
8.9
229
Not enough data
9.1
238
Connectivity
Not enough data
8.7
208
Not enough data
9.2
232
Not enough data
9.0
222
Not enough data
9.2
231
Operations
Not enough data
8.4
230
Not enough data
8.8
229
Not enough data
8.6
214
Not enough data
8.6
210
Not enough data
9.3
233
Building Reports
Not enough data
9.0
160
Not enough data
8.7
151
Not enough data
7.7
127
Not enough data
8.4
151
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Apache Airflow and Databricks are categorized as MLOps Platforms
Unique Categories
Apache Airflow is categorized as AI Orchestration
Databricks is categorized as DataOps Platforms, Data Governance, ETL Tools, Big Data Processing and Distribution, Big Data Analytics, Data Science and Machine Learning Platforms, Analytics Platforms, Data Warehouse, Database Management Systems (DBMS), Generative AI Infrastructure, AI Agent Builders, and AI Gateways
Reviews
Reviewers' Company Size
Apache Airflow
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Databricks
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
22.9%
Computer Software
16.9%
Financial Services
11.0%
Marketing and Advertising
4.2%
Banking
3.4%
Other
41.5%
Information Technology and Services
15.8%
Financial Services
10.4%
Computer Software
8.8%
Consulting
4.0%
Hospital & Health Care
3.7%
Other
57.4%
Alternatives
Discussions
What is airflow technology?
1 Comment
KS
Airflow is a orchestration tool which can be used to create, manage and run workflows and pipelines.Read more
Is Apache airflow an ETL tool?
1 Comment
BM
Yes, we can use it to schedule and trigger ETL jobs and orchestrate them into a logical workflow Read more
What is Lakehouse in Databricks?
4 Comments
BK
Lakehouse architecture is the merging of the data warehouse and data lake concepts into a single platform, with built-in support for lineage maintenance and ML.Read more
What are the features of Databricks?
4 Comments
SM
Delta Lake
Lakehosue platform
Schema evolution
Data quarantine & Data Quality
Data Integration & TransformationsRead more
What does Databricks software do?
3 Comments
SM
It will work like Hadoop, databricks provide the services like big data.
Databricks also work like in advanced level it's have capability to process large...Read more
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