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Compare Apache Kylin and Databricks Data Intelligence Platform 
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At a Glance
Market Segments
Small-Business (50.0% of reviews)
Enterprise (46.5% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Apache Kylin
Star Rating
(12)4.2 out of 5
Market Segments
Small-Business (50.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Apache KylinDatabricks Data Intelligence Platform
Star Rating
(626)4.6 out of 5
Market Segments
Enterprise (46.5% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Databricks Data Intelligence PlatformSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that the Databricks Data Intelligence Platform excels in Data Integration with a score of 9.0, allowing seamless connections to various data sources, while Apache Kylin, with a score of 8.9, is noted for its strong Data Management capabilities but lacks some of the flexibility in integration options.
- Reviewers mention that Databricks shines in Machine Learning Services, particularly with its support for Deep Learning at a score of 8.0, whereas Apache Kylin's capabilities in this area are more limited, with users noting a score of 8.3 for Deep Learning but lacking advanced features.
- G2 users highlight the superior Workflow Management in Databricks, scoring 9.3, which facilitates better project tracking and collaboration, while users on G2 report that Apache Kylin's workflow features are less intuitive, leading to a lower score of 8.4.
- Reviewers mention that Databricks offers robust Real-Time Analytics capabilities with a score of 8.5, making it ideal for businesses needing immediate insights, while Apache Kylin, with a score of 8.4, is seen as slightly behind in this area, particularly in handling large datasets efficiently.
- Users say that the Quality of Support for Databricks is rated at 8.4, with many praising the responsiveness and helpfulness of the support team, while Apache Kylin's support, although decent, scores lower at 8.2, with some users expressing concerns about response times.
- Reviewers mention that Databricks provides a more user-friendly experience with an Ease of Use score of 8.7, making it accessible for users of all skill levels, while Apache Kylin, with a score of 8.4, is noted for having a steeper learning curve, particularly for new users.
Pricing
Entry-Level Pricing
Apache Kylin
No pricing availableDatabricks Data Intelligence Platform
No pricing availableFree Trial
Apache Kylin
No trial information availableDatabricks Data Intelligence Platform
Free Trial is available
Ratings
Meets Requirements
Not enough data
8.9
512
Ease of Use
Not enough data
8.8
521
Ease of Setup
Not enough data
8.6
394
Ease of Admin
Not enough data
8.3
169
Quality of Support
Not enough data
8.7
487
Has the product been a good partner in doing business?
Not enough data
8.8
172
Product Direction (% positive)
Not enough data
9.6
500
Features by Category
Reports
Not enough data
7.5
6
Not enough data
7.5
6
Not enough data
7.8
6
Not enough data
7.7
5
Not enough data
8.0
5
Data Preparation
Not enough data
Not enough data
Not enough data
Not enough data
Data Modeling and Blending
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Analytics Platforms
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
Self Service
Not enough data
7.5
6
Not enough data
7.2
6
Not enough data
8.3
6
Not enough data
8.1
6
Not enough data
7.5
6
Not enough data
7.3
5
Deployment & Integration - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics
Not enough data
8.1
6
Not enough data
8.0
5
Not enough data
8.3
5
Performance & Scalability - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Capabilities - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Personalized Intelligence - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Building Reports
Not enough data
8.9
136
Not enough data
8.5
136
Not enough data
7.6
121
Not enough data
8.3
135
Administration
Not enough data
8.8
92
Not enough data
8.6
89
Not enough data
9.0
90
Not enough data
8.6
91
Management
Not enough data
8.5
84
Not enough data
8.7
83
Not enough data
8.6
83
Not enough data
8.5
82
Not enough data
8.7
82
Compliance
Not enough data
8.8
90
Not enough data
8.7
89
Not enough data
8.9
88
Not enough data
8.7
88
Security
Not enough data
9.0
80
Not enough data
8.9
82
Not enough data
8.9
82
Data Quality
Not enough data
9.0
90
Not enough data
8.7
89
Not enough data
9.0
87
Maintainence
Not enough data
8.8
81
Not enough data
8.8
80
Generative AI
Not enough data
8.4
79
Not enough data
8.5
78
Agentic AI - Data Governance
Not enough data
8.8
8
Not enough data
9.0
8
Not enough data
9.2
8
Not enough data
8.3
8
Not enough data
9.0
8
Not enough data
9.0
8
Management
Not enough data
8.6
167
Not enough data
8.5
161
Functionality
Not enough data
9.1
168
Not enough data
9.2
169
Not enough data
9.1
170
Not enough data
9.0
162
Not enough data
9.1
164
Deployment
Not enough data
8.9
63
Not enough data
8.9
64
Not enough data
8.9
64
Not enough data
8.9
64
Not enough data
8.9
64
Deployment
Not enough data
8.9
61
Not enough data
8.8
62
Not enough data
8.6
65
Not enough data
8.9
64
Not enough data
9.0
64
Management
Not enough data
8.9
61
Not enough data
8.8
63
Not enough data
9.1
59
Not enough data
8.9
67
Operations
Not enough data
8.7
61
Not enough data
8.8
60
Not enough data
9.0
61
Management
Not enough data
8.8
60
Not enough data
8.7
59
Not enough data
9.1
58
Generative AI
Not enough data
8.3
27
Not enough data
8.3
27
System
Not enough data
8.8
175
Model Development
Not enough data
8.8
179
Not enough data
7.9
185
Not enough data
8.3
182
Not enough data
8.6
184
Model Development
Not enough data
8.5
171
Machine/Deep Learning Services
Not enough data
8.1
171
Not enough data
8.5
176
Not enough data
8.2
168
Not enough data
8.1
170
Machine/Deep Learning Services
Not enough data
8.4
156
Not enough data
8.4
158
Deployment
Not enough data
8.5
174
Not enough data
8.7
177
Not enough data
9.0
181
Generative AI
Not enough data
8.2
86
Not enough data
8.4
86
Not enough data
7.6
85
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
9.2
6
Not enough data
8.6
6
Not enough data
8.6
6
Not enough data
8.9
6
Not enough data
9.2
6
Not enough data
9.2
6
Not enough data
9.2
6
Data Management
Not enough data
9.0
177
|
Verified
Not enough data
8.9
177
|
Verified
Not enough data
8.8
172
|
Verified
Not enough data
8.7
175
|
Verified
Not enough data
8.7
165
|
Verified
Not enough data
9.0
167
|
Verified
Integration
Not enough data
8.8
163
|
Verified
Not enough data
8.8
163
|
Verified
Not enough data
9.1
171
|
Verified
Deployment
Not enough data
7.9
152
|
Verified
Not enough data
9.1
173
|
Verified
Performance
Not enough data
9.1
173
|
Verified
Security
Not enough data
8.8
164
|
Verified
Not enough data
8.9
165
|
Verified
Generative AI
Not enough data
8.5
75
Not enough data
8.4
74
Data Management
Not enough data
9.0
66
Not enough data
8.7
65
Not enough data
8.8
66
Not enough data
9.1
63
Agentic AI - DataOps Platforms
Not enough data
8.6
6
Not enough data
8.6
6
Not enough data
9.2
6
Not enough data
8.6
6
Not enough data
9.2
6
Analytics
Not enough data
8.8
64
Not enough data
8.4
63
Monitoring and Management
Not enough data
8.5
64
Not enough data
8.5
64
Cloud Deployment
Not enough data
9.1
60
Not enough data
9.0
61
Generative AI
Not enough data
8.9
35
Not enough data
8.9
35
Database
Not enough data
8.7
218
Not enough data
8.9
224
Not enough data
9.3
225
Integrations
Not enough data
8.3
207
Not enough data
9.2
227
Platform
Not enough data
9.0
220
Not enough data
8.8
223
Not enough data
9.2
227
Processing
Not enough data
9.0
219
Not enough data
9.0
218
Data Transformation
Not enough data
8.8
219
Not enough data
9.0
226
Connectivity
Not enough data
8.7
202
Not enough data
9.2
225
Not enough data
9.0
217
Not enough data
9.2
225
Operations
Not enough data
8.4
223
Not enough data
8.8
218
Not enough data
8.6
207
Not enough data
8.6
205
Not enough data
9.3
220
Building Reports
Not enough data
8.9
136
Not enough data
8.5
136
Not enough data
7.6
121
Not enough data
8.3
135
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 Kylin and Databricks Data Intelligence Platform are categorized as Data Warehouse
Unique Categories
Apache Kylin has no unique categories
Databricks Data Intelligence Platform is categorized as MLOps Platforms, DataOps Platforms, Data Governance, ETL Tools, Big Data Processing and Distribution, Big Data Analytics, Data Science and Machine Learning Platforms, and Analytics Platforms
Reviews
Reviewers' Company Size
Apache Kylin
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
Information Technology and Services
16.7%
Computer Software
16.7%
Sports
8.3%
Retail
8.3%
Publishing
8.3%
Other
41.7%
Information Technology and Services
14.7%
Financial Services
11.4%
Computer Software
8.2%
Consulting
3.9%
Hospital & Health Care
3.8%
Other
58.1%
Alternatives
Discussions
Apache Kylin 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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