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Compare Monte Carlo and Soda 
At a Glance
Market Segments
Enterprise (50.8% of reviews)
Mid-Market (43.6% of reviews)
Entry-Level Pricing
Contact Us
$0.00 3 Production Datasets Per Month
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 plansSoda
Star Rating
(55)4.4 out of 5
Market Segments
Mid-Market (43.6% of reviews)
Pros & Cons
Entry-Level Pricing
$0.00 3 Production Datasets Per Month
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 Soda. Users appreciate its real-time alerts for data quality issues, which have greatly improved their ability to address problems proactively before stakeholders notice them.
- According to verified reviews, Monte Carlo has a much larger volume of feedback, with 460 reviews compared to Soda's 55. This suggests that users have a more reliable and comprehensive understanding of Monte Carlo's capabilities and performance.
- Users say that Soda shines with its clean and intuitive interface, making it easy for project managers to access necessary information quickly. This user-friendly design helps streamline data quality tasks and provides valuable real-time insights.
- Reviewers mention that while both products offer strong support, Soda's team has been particularly responsive, providing assistance via Slack. This direct interaction has been beneficial for users seeking quick answers to their questions, enhancing their overall experience.
- G2 reviewers highlight that Monte Carlo is continuously evolving, with users noting its frequent updates and new features that enhance usability. This commitment to improvement has made it a specialized tool for data monitoring and observability, which users find invaluable.
- According to recent feedback, while both products have their strengths, Soda's flexibility with an open-source implementation allows users to explore the tool without immediate financial commitment. This can be particularly appealing for teams looking to test the waters before investing in a full license.
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
Soda
Free
$0.00
3 Production Datasets Per Month
Great for small projects
- Pipeline testing
- Metrics observability
- Alerting & ticketing integrations
Free Trial
Monte Carlo
No trial information availableSoda
Free Trial is available
Ratings
Meets Requirements
8.3
436
8.7
49
Ease of Use
8.2
443
8.5
50
Ease of Setup
8.2
308
8.4
29
Ease of Admin
8.5
160
8.6
22
Quality of Support
9.0
390
8.7
49
Has the product been a good partner in doing business?
9.3
163
8.9
22
Product Direction (% positive)
8.9
432
9.0
49
Features by Category
Functionality
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
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
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
Not enough data
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
Functionality
7.4
291
8.0
22
8.8
323
9.2
24
8.1
294
8.1
24
8.0
299
8.8
24
Management
8.7
318
8.6
24
7.7
287
8.3
20
8.3
311
8.6
23
8.0
305
7.5
21
8.1
312
8.5
24
Generative AI
5.8
231
6.1
14
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
Functionality
8.1
187
8.7
42
6.4
174
Feature Not Available
6.7
169
8.0
41
6.1
164
Feature Not Available
6.4
165
7.9
43
Management
7.2
169
7.7
33
7.5
169
Feature Not Available
7.9
167
8.5
42
7.4
175
7.7
42
7.5
169
8.2
38
Generative AI
5.2
145
5.9
25
5.3
145
6.3
25
Categories
Categories
Shared Categories
Monte Carlo and Soda are categorized as Data Observability and Data Quality
Unique Categories
Monte Carlo is categorized as DataOps Platforms and Database Monitoring
Soda has no unique categories
Reviews
Reviewers' Company Size
Monte Carlo
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Soda
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%
Information Technology and Services
21.8%
Computer Software
18.2%
Consulting
16.4%
Financial Services
9.1%
Retail
3.6%
Other
30.9%
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
Soda has no discussions with answers
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