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Compare Monte Carlo and Secoda 
Featured Products
At a Glance
Market Segments
Enterprise (50.8% of reviews)
Mid-Market (69.2% of reviews)
Entry-Level Pricing
Contact Us
Contact Us Per Year
Monte 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 plansSecoda
Star Rating
(55)4.5 out of 5
Market Segments
Mid-Market (69.2% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us Per Year
Browse all 4 pricing plansMonte Carlo vs Secoda
When assessing the two solutions, reviewers found them equally easy to use. However, Secoda is easier to set up and administer. Reviewers also preferred doing business with Secoda overall.
- Monte Carlo and Secoda both meet the requirements of our reviewers at a comparable rate.
- When comparing quality of ongoing product support, reviewers felt that Secoda is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Secoda over Monte Carlo.
Pricing
Entry-Level Pricing
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
Secoda
Enterprise
Contact Us
Per Year
Built for bigger teams with security or deployment needs.
- Everything in Premium, plus:
- Unlimited integrations
- Custom user roles
Free Trial
Monte Carlo
No trial information availableSecoda
Free Trial is available
Ratings
Meets Requirements
8.3
436
8.3
31
Ease of Use
8.2
443
8.2
32
Ease of Setup
8.2
308
8.7
26
Ease of Admin
8.5
160
9.2
19
Quality of Support
9.0
390
9.7
30
Has the product been a good partner in doing business?
9.3
163
9.6
19
Product Direction (% positive)
8.9
432
9.2
30
Features by Category
Data Governance
Not enough data
8.7
5
Not enough data
9.0
5
Not enough data
8.9
9
Data Preparation
Not enough data
9.3
9
Not enough data
7.2
6
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Collaboration
Not enough data
9.2
6
Not enough data
9.3
5
Not enough data
9.3
9
Not enough data
9.5
7
Artificial Intelligence
Not enough data
Not enough data
Not enough data
8.1
6
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Machine Learning Data Catalog
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Feature Not Available
Administration
Not enough data
Feature Not Available
Not enough data
8.3
11
Not enough data
7.2
9
Not enough data
8.2
10
Management
Not enough data
9.1
11
Not enough data
9.1
11
Not enough data
8.0
11
Not enough data
7.5
10
Not enough data
8.8
11
Compliance
Not enough data
7.8
10
Not enough data
8.5
11
Not enough data
8.2
10
Not enough data
7.5
10
Security
Not enough data
8.6
11
Not enough data
8.3
11
Not enough data
7.5
10
Data Quality
Not enough data
7.3
10
Not enough data
6.2
10
Not enough data
6.8
10
Maintainence
Not enough data
8.5
10
Not enough data
7.8
10
Generative AI
Not enough data
5.6
6
Not enough data
5.3
5
Agentic AI - Data Governance
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
Functionality
9.0
260
Not enough data
8.8
261
Not enough data
7.8
238
Feature Not Available
8.3
247
Feature Not Available
7.7
242
Not enough data
7.4
244
Not enough data
Agentic AI - Database Monitoring
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
Not enough data
Functionality
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
Not enough data
Not enough data
Functionality
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
Feature Not Available
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
Agentic AI - Sensitive Data Discovery
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management
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
Security
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 - Data Fabric
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
Responses
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Automation - AI Agents
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
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Autonomy - AI Agents
Not enough data
Not enough data
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
Data Management
8.5
51
Not enough data
8.4
47
Not enough data
8.6
51
Not enough data
7.9
49
Not enough data
Agentic AI - DataOps Platforms
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
Not enough data
Analytics
7.8
50
Not enough data
7.7
47
Not enough data
Monitoring and Management
9.2
55
Not enough data
7.6
48
Feature Not Available
Cloud Deployment
7.4
43
Not enough data
7.0
41
Not enough data
Generative AI
6.2
34
Not enough data
6.1
34
Not enough data
Data management
Not enough data
9.3
10
Not enough data
7.0
11
Not enough data
7.8
10
Not enough data
8.2
10
Not enough data
8.2
11
Reporting
Not enough data
5.4
9
Not enough data
6.5
10
Not enough data
6.3
10
Generative AI
Not enough data
5.2
7
Not enough data
4.5
7
Functionality
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Functionality
7.4
291
Not enough data
8.8
323
Not enough data
8.1
294
Not enough data
8.0
299
Not enough data
Management
8.7
318
Not enough data
7.7
287
Not enough data
8.3
311
Not enough data
8.0
305
Not enough data
8.1
312
Not enough data
Generative AI
5.8
231
Not enough data
Agentic AI - Data Observability
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
Not enough data
Agentic AI - AI Agents
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
Functionality
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
Not enough data
Management
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
Not enough data
Generative AI
5.2
145
Not enough data
5.3
145
Not enough data
Categories
Categories
Shared Categories
Monte Carlo and Secoda are categorized as DataOps Platforms, Database Monitoring, Data Observability, and Data Quality
Unique Categories
Monte Carlo has no unique categories
Reviews
Reviewers' Company Size
Monte Carlo
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Secoda
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
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%
Computer Software
19.2%
Financial Services
17.3%
Information Technology and Services
15.4%
Hospitality
5.8%
Health, Wellness and Fitness
5.8%
Other
36.5%
Alternatives
Discussions
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
Secoda has no discussions with answers
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