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Compare Apache Beam and Databricks Data Intelligence Platform 
Featured Products
At a Glance
Market Segments
Mid-Market (42.9% of reviews)
Enterprise (46.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Apache Beam
Star Rating
(16)4.1 out of 5
Market Segments
Mid-Market (42.9% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache BeamDatabricks Data Intelligence Platform
Star Rating
(658)4.6 out of 5
Market Segments
Enterprise (46.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Databricks Data Intelligence PlatformSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that the Databricks Data Intelligence Platform excels in overall user satisfaction, boasting a significantly higher G2 Score compared to Apache Beam. Users appreciate its ability to scale large language models and manage data across multiple cloud environments seamlessly.
- Users say that Databricks offers a more intuitive interface, with interactive notebooks that support SQL and Python for data visualization, making it easier for teams to collaborate and analyze data effectively. In contrast, while Apache Beam provides a unified approach to batch and stream processing, some users find its learning curve steeper.
- Reviewers mention that the autoscaling feature in Databricks is particularly beneficial, helping to optimize cloud resource costs without compromising performance. This feature has been highlighted as a game-changer for users who are new to autoscaling, whereas Apache Beam does not have a comparable feature that stands out in user feedback.
- According to verified reviews, the quality of support for Databricks is rated highly, with users noting timely assistance and effective problem resolution. In contrast, Apache Beam's support has received mixed feedback, with some users expressing a desire for more robust support options.
- Users highlight that Databricks is particularly strong in data lake integration and Spark integration, with scores reflecting its effectiveness in these areas. Apache Beam, while capable, does not match the same level of integration ease, especially for users looking to leverage Spark's capabilities.
- Reviewers appreciate Apache Beam's unique abstraction for distributed processing, which simplifies complex tasks. However, they also note that the overall user experience is less favorable compared to Databricks, which consistently receives higher ratings for ease of use and setup.
Pricing
Entry-Level Pricing
Apache Beam
No pricing availableDatabricks Data Intelligence Platform
No pricing availableFree Trial
Apache Beam
No trial information availableDatabricks Data Intelligence Platform
Free Trial is available
Ratings
Meets Requirements
8.6
12
8.9
538
Ease of Use
7.8
12
8.9
549
Ease of Setup
Not enough data
8.7
422
Ease of Admin
Not enough data
8.3
176
Quality of Support
7.6
11
8.7
513
Has the product been a good partner in doing business?
Not enough data
8.9
180
Product Direction (% positive)
8.1
12
9.6
527
Features by Category
Reports
Not enough data
8.2
11
Not enough data
7.4
9
Not enough data
8.3
11
Not enough data
8.0
9
Not enough data
8.8
12
Data Preparation
Not enough data
8.9
6
Not enough data
8.8
7
Data Modeling and Blending
Not enough data
9.0
8
Not enough data
8.8
7
Not enough data
8.8
8
Generative AI
Not enough data
9.0
8
Not enough data
9.2
6
Agentic AI - Analytics Platforms
Not enough data
9.3
7
Not enough data
8.7
5
Not enough data
9.0
5
Not enough data
8.3
6
Not enough data
8.1
6
Not enough data
9.7
6
Not enough data
9.3
5
Self Service
Not enough data
7.7
10
Not enough data
7.7
10
Not enough data
8.3
10
Not enough data
7.9
11
Not enough data
8.2
11
Not enough data
7.9
8
Deployment & Integration - Analytics Platforms
Not enough data
8.1
7
Not enough data
9.2
8
Not enough data
8.6
6
Not enough data
9.2
6
Advanced Analytics
Not enough data
8.2
10
Not enough data
8.2
11
Not enough data
8.8
10
Performance & Scalability - Analytics Platforms
Not enough data
8.8
7
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
8.8
7
Not enough data
8.3
7
Not enough data
8.6
6
Agentic AI Capabilities - Analytics Platforms
Not enough data
8.6
7
Not enough data
8.8
7
Not enough data
8.9
6
Not enough data
8.6
7
Personalized Intelligence - Analytics Platforms
Not enough data
9.2
6
Not enough data
7.9
8
Not enough data
8.9
6
Building Reports
Not enough data
8.9
137
Not enough data
8.6
137
Not enough data
7.6
122
Not enough data
8.4
140
Administration
Not enough data
8.8
97
Not enough data
8.6
93
Not enough data
9.0
93
Not enough data
8.7
95
Management
Not enough data
8.4
87
Not enough data
8.6
86
Not enough data
8.6
87
Not enough data
8.5
87
Not enough data
8.7
85
Compliance
Not enough data
8.8
97
Not enough data
8.7
92
Not enough data
8.8
92
Not enough data
8.7
93
Security
Not enough data
9.0
85
Not enough data
8.9
85
Not enough data
8.8
86
Data Quality
Not enough data
9.0
93
Not enough data
8.7
93
Not enough data
8.9
92
Maintainence
Not enough data
8.7
85
Not enough data
8.8
83
Generative AI
Not enough data
8.4
82
Not enough data
8.5
81
Agentic AI - Data Governance
Not enough data
8.5
10
Not enough data
8.8
11
Not enough data
9.0
14
Not enough data
8.5
12
Not enough data
9.0
12
Not enough data
9.0
13
Management
Not enough data
8.6
169
Not enough data
8.5
163
Functionality
Not enough data
9.1
170
Not enough data
9.2
170
Not enough data
9.1
171
Not enough data
9.0
163
Not enough data
9.1
165
Deployment
Not enough data
8.9
64
Not enough data
8.9
64
Not enough data
8.9
64
Not enough data
8.9
65
Not enough data
8.9
66
Deployment
Not enough data
8.9
61
Not enough data
8.8
62
Not enough data
8.6
66
Not enough data
8.9
65
Not enough data
9.0
66
Management
Not enough data
9.0
62
Not enough data
8.8
63
Not enough data
9.1
59
Not enough data
8.9
67
Operations
Not enough data
8.7
62
Not enough data
8.8
61
Not enough data
9.0
62
Management
Not enough data
8.8
60
Not enough data
8.7
60
Not enough data
9.1
59
Generative AI
Not enough data
8.3
28
Not enough data
8.3
28
System
Not enough data
8.8
178
Model Development
Not enough data
8.8
182
Not enough data
7.9
187
Not enough data
8.3
184
Not enough data
8.6
187
Model Development
Not enough data
8.5
171
Machine/Deep Learning Services
Not enough data
8.2
173
Not enough data
8.5
179
Not enough data
8.2
170
Not enough data
8.2
172
Machine/Deep Learning Services
Not enough data
8.4
158
Not enough data
8.4
160
Deployment
Not enough data
8.5
176
Not enough data
8.7
179
Not enough data
9.0
185
Generative AI
Not enough data
8.2
86
Not enough data
8.4
87
Not enough data
7.6
86
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
9.2
8
Not enough data
8.3
7
Not enough data
8.1
8
Not enough data
8.6
7
Not enough data
9.1
9
Not enough data
9.2
6
Not enough data
9.3
7
Data Management
Not enough data
9.0
181
|
Verified
Not enough data
8.9
180
|
Verified
Not enough data
8.8
174
|
Verified
Not enough data
8.8
178
|
Verified
Not enough data
8.7
167
|
Verified
Not enough data
9.1
170
|
Verified
Integration
Not enough data
8.8
167
|
Verified
Not enough data
8.8
165
|
Verified
Not enough data
9.1
172
|
Verified
Deployment
Not enough data
7.9
155
|
Verified
Not enough data
9.1
176
|
Verified
Performance
Not enough data
9.1
176
|
Verified
Security
Not enough data
8.8
165
|
Verified
Not enough data
8.9
166
|
Verified
Generative AI
Not enough data
8.5
76
Not enough data
8.4
75
Data Management
Not enough data
9.0
66
Not enough data
8.7
67
Not enough data
8.8
67
Not enough data
9.1
66
Agentic AI - DataOps Platforms
Not enough data
9.0
8
Not enough data
8.6
6
Not enough data
9.0
7
Not enough data
8.6
6
Not enough data
9.3
7
Analytics
Not enough data
8.8
66
Not enough data
8.5
64
Monitoring and Management
Not enough data
8.6
66
Not enough data
8.6
66
Cloud Deployment
Not enough data
9.1
62
Not enough data
9.0
62
Generative AI
Not enough data
8.9
35
Not enough data
8.9
35
Database
7.7
10
8.7
229
8.0
10
8.9
235
7.1
7
9.3
242
Integrations
6.0
5
8.3
217
7.3
5
9.1
244
Platform
8.3
6
9.0
236
8.1
7
8.8
234
7.3
5
9.1
244
Processing
8.2
10
9.0
233
8.1
7
9.0
230
Data Transformation
Not enough data
8.8
223
Not enough data
9.0
229
Connectivity
Not enough data
8.7
205
Not enough data
9.2
229
Not enough data
9.0
219
Not enough data
9.2
227
Operations
Not enough data
8.4
225
Not enough data
8.8
220
Not enough data
8.6
210
Not enough data
8.6
209
Not enough data
9.3
224
Building Reports
Not enough data
8.9
137
Not enough data
8.6
137
Not enough data
7.6
122
Not enough data
8.4
140
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 Beam and Databricks Data Intelligence Platform are categorized as Big Data Processing and Distribution
Unique Categories
Apache Beam has no unique categories
Databricks Data Intelligence Platform is categorized as MLOps Platforms, DataOps Platforms, Data Governance, ETL Tools, Big Data Analytics, Data Science and Machine Learning Platforms, Data Warehouse, and Analytics Platforms
Reviews
Reviewers' Company Size
Apache Beam
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Databricks Data Intelligence Platform
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
Retail
14.3%
Logistics and Supply Chain
14.3%
Information Technology and Services
14.3%
Computer Software
14.3%
Telecommunications
7.1%
Other
35.7%
Information Technology and Services
15.1%
Financial Services
11.1%
Computer Software
8.3%
Consulting
3.7%
Hospital & Health Care
3.6%
Other
58.2%
Alternatives
Discussions
Apache Beam has no discussions with answers
What is Lakehouse in Databricks?
4 Comments
BR
Lakehouse is a new and open data management architecture solution that combines the best features of the data lake and warehouse.Read more
What are the features of Databricks?
3 Comments
SA
It supports large amount of data with capability to write code in SQL, Spark, Python and R.
In the backend, it stored the data in the parquet file which...Read more
What is Databricks unified analytics platform?
3 Comments
CA
Databricks' Unified Data Analytics Platform helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks...Read more
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