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Compare Cube and Datarails 
Featured Products
At a Glance
Market Segments
Mid-Market (80.5% of reviews)
Mid-Market (73.0% of reviews)
Entry-Level Pricing
No pricing available
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Cube
Star Rating
(123)4.5 out of 5
Market Segments
Mid-Market (80.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about CubeDatarails
Star Rating
(267)4.6 out of 5
Market Segments
Mid-Market (73.0% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Datarails excels in financial reporting and analysis, with users highlighting its ability to streamline these processes effectively. One user noted that the platform made their budget season much smoother, showcasing its strength in handling complex financial tasks.
- Users say Cube stands out for its fast and flexible budgeting and forecasting capabilities. Reviewers appreciate how it integrates seamlessly with existing systems, allowing for real-time data retrieval, which enhances efficiency in analysis rather than data manipulation.
- According to verified reviews, Datarails has a higher overall satisfaction score, reflecting its strong performance in financial analysis and reporting. Users have praised its centralized data warehouse capabilities, which allow for the integration of multiple data sources, making it a robust choice for financial teams.
- Reviewers mention that Cube's implementation process is refreshingly simple and quick, with minimal ramp-up time required. This ease of setup is frequently highlighted, making it an attractive option for teams looking to get started without extensive delays.
- G2 reviewers note that while Datarails has a slight edge in overall user satisfaction, Cube's customer support is frequently praised as one of the best, with users describing their support team as responsive and knowledgeable, which can be crucial during the implementation phase.
- Users report that Datarails shines in its ability to consolidate data from various sources, which is a significant advantage for companies needing a comprehensive view of their financials. In contrast, Cube is recognized for its strong budgeting features, but some users feel it could improve in areas like data visualization.
Pricing
Entry-Level Pricing
Cube
No pricing availableDatarails
Datarails FP&A Premium
Contact Us
- FinanceOS FP&A
- 5 users
- 2 integrations
Free Trial
Cube
No trial information availableDatarails
No trial information availableRatings
Meets Requirements
8.5
99
8.7
238
Ease of Use
8.9
99
7.9
245
Ease of Setup
8.6
52
7.5
206
Ease of Admin
9.0
47
8.2
159
Quality of Support
9.1
98
9.3
235
Has the product been a good partner in doing business?
9.3
49
9.2
158
Product Direction (% positive)
8.9
92
9.4
243
Features by Category
Budget Creation
8.2
62
9.0
153
8.6
57
8.4
135
8.6
59
8.8
134
8.2
61
8.5
144
8.0
48
7.8
112
8.8
56
8.7
138
Budget Management
8.7
50
8.7
142
8.2
49
8.3
127
8.1
43
8.0
123
Forecasting
8.8
56
8.8
136
8.9
48
8.2
126
8.6
48
8.3
124
8.4
49
8.2
123
7.7
10
6.7
87
Analytics
8.7
58
8.4
136
8.7
53
8.4
127
8.5
49
8.2
117
Agentic AI - Budgeting and Forecasting
Not enough data
7.1
32
Not enough data
7.0
32
Not enough data
7.4
34
Data Management
8.3
59
9.1
162
8.8
53
9.0
165
8.5
55
8.5
157
Reporting Structure
8.7
50
8.5
139
8.1
49
8.1
146
8.3
46
8.4
147
Standard Analytics
8.1
42
8.3
134
8.0
46
8.3
144
8.6
56
8.6
149
8.4
59
8.9
155
Custom Analytics
6.6
50
8.4
152
7.5
50
8.4
133
8.6
54
8.8
149
8.7
53
8.2
147
8.3
10
8.6
101
Agentic AI - Financial Analysis
Not enough data
7.3
28
Not enough data
7.1
27
Cash Flow Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cash Flow Forecasting
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
Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Financial Data Transfer
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
8.7
5
Agentic AI - Cash Flow Management
Not enough data
Not enough data
Reconciliation
9.1
32
8.8
75
|
Verified
9.1
31
8.7
74
|
Verified
8.6
25
8.8
34
Reporting
9.1
33
8.4
77
|
Verified
8.8
30
8.1
78
|
Verified
9.1
32
8.4
76
|
Verified
Closing Process
8.8
18
7.6
61
|
Verified
8.3
18
7.0
60
|
Verified
9.0
24
7.8
62
|
Verified
AI - Financial Close
Not enough data
6.1
11
Not enough data
6.4
11
Not enough data
6.2
11
Not enough data
6.3
10
Not enough data
5.9
11
Financial Planning
8.8
12
8.0
78
|
Verified
9.1
19
8.8
86
|
Verified
8.3
17
8.6
87
|
Verified
Agentic AI - FP&A (Financial Planning & Analysis)
Not enough data
6.7
27
Not enough data
7.0
27
Financial Insight
9.4
18
8.2
93
|
Verified
8.9
19
8.0
93
|
Verified
9.2
20
8.0
92
|
Verified
Data
7.2
20
8.6
99
|
Verified
8.4
20
8.8
100
|
Verified
9.4
21
9.1
105
|
Verified
8.4
19
8.2
97
|
Verified
Status Communication
8.4
20
8.3
93
|
Verified
9.4
19
9.1
94
|
Verified
7.9
16
9.0
98
|
Verified
7.8
12
8.1
30
Reconciliation - Financial Reconciliation
Not enough data
9.2
6
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Audit - Financial Reconciliation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integrations - Financial Reconciliation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
User Permissions and Security - Financial Reconciliation
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Financial Reconciliation
Not enough data
Not enough data
Agentic AI - Accounting & Finance
Not enough data
Not enough data
Categories
Categories
Shared Categories
Cube and Datarails are categorized as Financial Close, FP&A (Financial Planning & Analysis), Budgeting and Forecasting, and Financial Analysis
Unique Categories
Cube has no unique categories
Datarails is categorized as Cash Flow Management and Financial Reconciliation
Reviews
Reviewers' Company Size
Cube
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Datarails
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
13.0%
Computer Software
12.2%
Financial Services
9.8%
Marketing and Advertising
4.1%
Health, Wellness and Fitness
4.1%
Other
56.9%
Financial Services
8.0%
Hospital & Health Care
7.2%
Manufacturing
5.7%
Accounting
4.6%
Oil & Energy
4.2%
Other
70.3%
Discussions
Cube has no discussions with answers
Datarails has no discussions with answers
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