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Compare IBM Databand and Monte Carlo 
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At a Glance
Market Segments
Mid-Market (39.4% of reviews)
Enterprise (51.3% of reviews)
Entry-Level Pricing
Contact Us 1 GB / Month of Metadata Logged Per Year
Contact Us
IBM Databand
Star Rating
(67)4.4 out of 5
Market Segments
Mid-Market (39.4% of reviews)
Entry-Level Pricing
Contact Us 1 GB / Month of Metadata Logged Per Year
Browse all 2 pricing plansMonte Carlo
Star Rating
(435)4.4 out of 5
Market Segments
Enterprise (51.3% of reviews)
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that IBM Databand excels in data quality monitoring with a score of 8.6, while Monte Carlo shines in the same area with a slightly higher score of 8.9, indicating that Monte Carlo may offer more robust features for ensuring data integrity.
- Reviewers mention that IBM Databand provides excellent data observability with a score of 9.3, which is significantly higher than Monte Carlo's score of 8.1, suggesting that users may find IBM Databand more effective for tracking data flow and anomalies.
- G2 users highlight that IBM Databand's self-service capabilities score an impressive 8.9, making it easier for users to manage their data without heavy reliance on IT, whereas Monte Carlo's self-service features are less emphasized.
- Users on G2 report that IBM Databand's real-time alerts feature scores 8.6, providing timely notifications, while Monte Carlo's score of 8.3 indicates it may not be as responsive, which could impact users needing immediate insights.
- Reviewers say that IBM Databand's ease of setup is rated at 8.3, which is slightly lower than Monte Carlo's 8.4, suggesting that users may find Monte Carlo a bit easier to implement initially.
- Users report that the quality of support for Monte Carlo is rated at 9.3, which is higher than IBM Databand's score of 8.9, indicating that users may experience better assistance and resources when using Monte Carlo.
Pricing
Entry-Level Pricing
IBM Databand
Growth
Contact Us
1 GB / Month of Metadata Logged Per Year
- Monitored Pipelines | < 100
- Metadata Logged | Up to 500MB / month
- Alerting | Email. Slack. Pagerduty. Opsgenie
Monte Carlo
Start
Contact Us
All you need to make data reliable for one team
- Monitoring for Data Warehouse, Business Intelligence, ETL
- Incident triaging, troubleshooting and root cause analysis
- Lineage
Free Trial
IBM Databand
Free Trial is available
Monte Carlo
No trial information availableRatings
Meets Requirements
8.6
60
8.3
410
Ease of Use
8.6
62
8.2
417
Ease of Setup
8.3
31
8.2
281
Ease of Admin
8.0
23
8.5
148
Quality of Support
8.9
58
9.0
367
Has the product been a good partner in doing business?
8.3
23
9.3
149
Product Direction (% positive)
9.4
58
8.9
406
Features by Category
Data Source Access
8.6
27
Not enough data
8.6
29
Not enough data
8.8
28
Not enough data
Data Interaction
8.3
27
Not enough data
8.5
29
Not enough data
8.4
29
Not enough data
8.8
28
Not enough data
8.7
28
Not enough data
9.0
29
Not enough data
8.6
28
Not enough data
8.6
29
Not enough data
Data Exporting
8.5
27
Not enough data
8.2
28
Not enough data
8.8
29
Not enough data
Generative AI
8.5
8
Not enough data
Functionality
Not enough data
9.0
258
Not enough data
8.8
258
Not enough data
7.8
237
Not enough data
8.3
246
Not enough data
7.6
241
Not enough data
7.4
243
Agentic AI - Database Monitoring
Not enough data
7.1
13
Not enough data
6.9
13
Not enough data
6.9
13
Not enough data
7.1
13
Not enough data
6.8
12
Not enough data
6.5
13
Not enough data
7.1
13
Data Management
Not enough data
8.5
51
Not enough data
8.4
47
Not enough data
8.6
51
Not enough data
7.9
49
Agentic AI - DataOps Platforms
Not enough data
6.7
5
Not enough data
6.0
5
Not enough data
6.3
5
Not enough data
6.3
5
Not enough data
6.3
5
Analytics
Not enough data
7.8
49
Not enough data
7.7
47
Monitoring and Management
Not enough data
9.1
52
Not enough data
7.6
48
Cloud Deployment
Not enough data
7.4
43
Not enough data
7.0
41
Generative AI
Not enough data
6.2
34
Not enough data
6.1
34
Functionality
8.6
46
7.3
287
8.6
45
8.8
309
8.2
45
8.1
291
8.9
46
8.0
294
Management
8.3
45
8.7
305
8.3
42
7.7
283
8.5
44
8.2
297
8.7
42
8.0
300
8.6
44
8.1
302
Generative AI
7.3
11
5.8
230
Agentic AI - Data Observability
Not enough data
6.1
27
Not enough data
6.2
27
Not enough data
6.7
27
Not enough data
6.4
26
Not enough data
6.4
27
Functionality
Not enough data
8.0
177
Not enough data
6.4
171
Not enough data
6.6
166
Not enough data
6.0
161
Not enough data
6.4
162
Management
Not enough data
7.2
164
Not enough data
7.4
165
Not enough data
7.9
164
Not enough data
7.3
169
Not enough data
7.5
164
Generative AI
Not enough data
5.2
142
Not enough data
5.2
141
Categories
Categories
Shared Categories
IBM Databand and Monte Carlo are categorized as Data Observability
Reviews
Reviewers' Company Size
IBM Databand
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Monte Carlo
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
22.7%
Computer Software
19.7%
Retail
9.1%
Computer & Network Security
7.6%
Financial Services
6.1%
Other
34.8%
Financial Services
14.8%
Computer Software
11.1%
Information Technology and Services
10.7%
Marketing and Advertising
3.7%
Pharmaceuticals
3.5%
Other
56.1%
Discussions
IBM Databand has no discussions with answers
What is Monte Carlo software?
1 Comment
MV
Monte Carlo is a fully automated, end-to-end data observability platform that helps data engineering teams reduce time to detection and resolution for data...Read more
Monte Carlo has no more discussions with answers
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