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Compare Anomalo and Monte Carlo 
At a Glance
Market Segments
Enterprise (50.0% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
Contact Us 10000 Tables Per Year
Contact Us
Anomalo
Star Rating
(41)4.4 out of 5
Market Segments
Enterprise (50.0% of reviews)
Entry-Level Pricing
Contact Us 10000 Tables Per Year
Learn more about AnomaloMonte Carlo
Star Rating
(406)4.4 out of 5
Market Segments
Enterprise (50.0% 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 Monte Carlo excels in monitoring capabilities with a score of 9.1, while Anomalo trails behind at 8.1. Reviewers mention that Monte Carlo's real-time monitoring features provide a comprehensive view of data health, making it easier to identify issues promptly.
- Reviewers mention that Anomalo shines in data quality monitoring with a score of 9.4, compared to Monte Carlo's 8.9. Users on G2 appreciate Anomalo's robust data quality checks, which help ensure data integrity across various sources.
- Users say that Monte Carlo offers superior alerting features, scoring 8.8, while Anomalo's alerting capabilities are rated at 7.9. Reviewers highlight that Monte Carlo's alert system is more intuitive and customizable, allowing for tailored notifications based on specific data conditions.
- G2 users report that Anomalo has a better score in anomaly identification at 9.3 compared to Monte Carlo's 8.8. Users mention that Anomalo's algorithms are particularly effective at detecting subtle anomalies, which can be crucial for maintaining data accuracy.
- Reviewers mention that Monte Carlo's ease of setup is rated at 8.4, while Anomalo significantly outperforms with a score of 9.4. Users report that Anomalo's onboarding process is streamlined and user-friendly, making it easier for teams to get started quickly.
- Users on G2 highlight that Monte Carlo's quality of support is rated at 9.3, which is higher than Anomalo's 9.0. Reviewers say that Monte Carlo's support team is responsive and knowledgeable, providing valuable assistance during critical issues.
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Pricing
Entry-Level Pricing
Anomalo
Custom
Contact Us
10000 Tables Per Year
Free pilot. Secure In-VPC deployment. Contact us to get started.
- Automated data monitoring
- Simple installation
- Visualizations for reporting and explainability
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
Anomalo
Free Trial is available
Monte Carlo
No trial information availableRatings
Meets Requirements
8.2
36
8.3
381
Ease of Use
8.5
36
8.2
388
Ease of Setup
9.4
14
8.3
254
Ease of Admin
8.1
15
8.6
142
Quality of Support
9.0
35
9.0
341
Has the product been a good partner in doing business?
8.9
15
9.4
143
Product Direction (% positive)
8.8
29
8.9
377
Features by Category
Functionality
8.1
7
9.0
246
7.9
7
8.8
245
6.0
5
7.8
225
6.9
6
8.3
233
7.2
6
7.7
229
7.9
7
7.5
230
Agentic AI - Database Monitoring
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
Data Management
Not enough data
8.6
46
Not enough data
8.6
42
Not enough data
8.7
46
Not enough data
7.9
44
Agentic AI - DataOps Platforms
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
7.8
44
Not enough data
7.7
42
Monitoring and Management
Not enough data
9.2
47
Not enough data
7.7
43
Cloud Deployment
Not enough data
7.5
38
Not enough data
7.0
36
Generative AI
Not enough data
6.3
29
Not enough data
6.1
29
Functionality
Not enough data
7.3
259
9.4
6
8.8
282
7.8
6
8.1
265
8.7
5
8.1
268
Management
9.3
7
8.7
278
8.0
5
7.8
256
8.6
6
8.2
270
Not enough data
8.0
273
7.1
7
8.2
275
Generative AI
Not enough data
5.9
204
Agentic AI - Data Observability
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
8.7
14
8.1
153
Feature Not Available
6.4
148
Feature Not Available
6.7
143
6.9
7
6.0
138
7.8
10
6.4
139
Management
8.7
15
7.2
141
7.8
18
7.5
142
8.5
14
7.9
141
8.6
16
7.4
146
7.4
12
7.5
141
Generative AI
Not enough data
5.3
121
Not enough data
5.3
120
Categories
Categories
Shared Categories
Anomalo and Monte Carlo are categorized as Data Quality, Data Observability, and Database Monitoring
Reviews
Reviewers' Company Size
Anomalo
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
Financial Services
22.5%
Information Technology and Services
12.5%
Computer Software
12.5%
Leisure, Travel & Tourism
7.5%
Internet
7.5%
Other
37.5%
Financial Services
13.7%
Information Technology and Services
11.4%
Computer Software
11.2%
Pharmaceuticals
3.7%
Online Media
3.5%
Other
56.5%
Most Helpful Reviews
Anomalo
Most Helpful Favorable Review
Verified User in Financial Services
That it's an end-to-end anomaly detection service.
Most Helpful Critical Review
Stav H.
Verified User in Marketing and Advertising
Admin page is very not user friendly Many bugs Tables are not immediately updated in the system Team does not respond to feature requests or bug reports UI is bad
Monte Carlo
Most Helpful Favorable Review
Lior S.
Verified User in Computer Software
I enjoy the fact we don't need to proactively set up monitors for each new table or important metric in our data warehouse. Monte Carlo by default tracks all your tables in your data warehouse.
Most Helpful Critical Review
Verified User in Program Development
We see some limitations still to add all the filters
Verified User in Financial Services
That it's an end-to-end anomaly detection service.
Lior S.
Verified User in Computer Software
I enjoy the fact we don't need to proactively set up monitors for each new table or important metric in our data warehouse. Monte Carlo by default tracks all your tables in your data warehouse.
Stav H.
Verified User in Marketing and Advertising
Admin page is very not user friendly Many bugs Tables are not immediately updated in the system Team does not respond to feature requests or bug reports UI is bad
Verified User in Program Development
We see some limitations still to add all the filters
Discussions
Anomalo 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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