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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 (50.8% 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)
Pros & Cons
Entry-Level Pricing
Contact Us 1 GB / Month of Metadata Logged Per Year
Browse all 2 pricing plansMonte Carlo
Star Rating
(469)4.4 out of 5
Market Segments
Enterprise (50.8% 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 Monte Carlo excels in overall user satisfaction, boasting a significantly higher G2 Score compared to IBM Databand. This reflects a broader consensus among users who appreciate its robust data monitoring capabilities.
- Users say that IBM Databand is particularly effective for timely data delivery, with features that allow for monitoring data pipeline errors, such as failed runs and unexpected schema changes, making it a reliable choice for teams focused on data integrity.
- Reviewers mention that Monte Carlo's real-time alerts for data quality issues have transformed their data management processes, enabling teams to proactively address problems before they impact stakeholders, which is a standout feature that enhances data reliability.
- According to verified reviews, both products are user-friendly, but IBM Databand receives praise for its intuitive design and ease of use, making it accessible for teams looking to streamline their data operations without a steep learning curve.
- Users highlight that while IBM Databand has strong capabilities in data extraction and transformation, Monte Carlo's continuous feature updates and focus on data observability make it a more dynamic tool for organizations needing to adapt quickly to changing data landscapes.
- Reviewers note that IBM Databand's quality of support is highly rated, with users appreciating the assistance they receive, while Monte Carlo also garners positive feedback for its support, indicating that both products prioritize customer service, though Monte Carlo's larger user base may offer more community-driven insights.
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
436
Ease of Use
8.6
62
8.2
443
Ease of Setup
8.3
31
8.2
308
Ease of Admin
8.0
23
8.5
160
Quality of Support
8.9
58
9.0
390
Has the product been a good partner in doing business?
8.3
23
9.3
163
Product Direction (% positive)
9.4
58
8.9
432
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
260
Not enough data
8.8
261
Not enough data
7.8
238
Not enough data
8.3
247
Not enough data
7.7
242
Not enough data
7.4
244
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
7.2
6
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
50
Not enough data
7.7
47
Monitoring and Management
Not enough data
9.2
55
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
7.4
291
8.6
45
8.8
323
8.2
45
8.1
294
8.9
46
8.0
299
Management
8.3
45
8.7
318
8.3
42
7.7
287
8.5
44
8.3
311
8.7
42
8.0
305
8.6
44
8.1
312
Generative AI
7.3
11
5.8
231
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
6.7
29
Functionality
Not enough data
8.1
187
Not enough data
6.4
174
Not enough data
6.7
169
Not enough data
6.1
164
Not enough data
6.4
165
Management
Not enough data
7.2
169
Not enough data
7.5
169
Not enough data
7.9
167
Not enough data
7.4
175
Not enough data
7.5
169
Generative AI
Not enough data
5.2
145
Not enough data
5.3
145
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
14.2%
Information Technology and Services
11.2%
Computer Software
10.7%
Marketing and Advertising
3.7%
Manufacturing
3.5%
Other
56.7%
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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