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Compare Bigeye and Monte Carlo

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At a Glance
Bigeye
Bigeye
Star Rating
(22)4.1 out of 5
Market Segments
Small-Business (54.5% of reviews)
Information
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about Bigeye
Monte Carlo
Monte Carlo
Star Rating
(469)4.4 out of 5
Market Segments
Enterprise (50.8% of reviews)
Information
Pros & Cons
Entry-Level Pricing
Contact Us
Browse all 3 pricing plans
AI Generated Summary
AI-generated. Powered by real user reviews.
  • G2 reviewers report that Monte Carlo excels in data observability, receiving high praise for its real-time alerts that enhance awareness of data quality issues. Users appreciate how these alerts allow teams to proactively address problems before they escalate, significantly improving data reliability.
  • Users say that Bigeye offers a user-friendly experience, with its core concepts being simple and easy to grasp. This accessibility is complemented by more technical features, making it a versatile choice for both novice and advanced users looking to monitor data quality.
  • According to verified reviews, Monte Carlo's implementation process is notably efficient, with many users highlighting its intuitive onboarding features. This ease of setup helps teams quickly integrate the tool into their workflows, enhancing overall productivity.
  • Reviewers mention that while Bigeye provides solid functionality for creating freshness and volume checks, it may not match the comprehensive monitoring capabilities of Monte Carlo. Users have noted that Monte Carlo's specialized focus on data observability leads to a more robust solution for ongoing data management.
  • G2 reviewers highlight the quality of support provided by Monte Carlo, which is rated highly by users. Many have expressed satisfaction with the responsiveness and helpfulness of the support team, contributing to a positive overall experience with the product.
  • Users report that Bigeye shines in its ability to perform custom checks via SQL, which adds significant value for users who need tailored monitoring solutions. However, some users feel that its overall feature set may not be as comprehensive as that of Monte Carlo, particularly in the realm of data observability.
Pricing
Entry-Level Pricing
Bigeye
Enterprise Starter
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Learn more about Bigeye
Monte Carlo
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Free Trial
Bigeye
No trial information available
Monte Carlo
No trial information available
Ratings
Meets Requirements
8.0
22
8.3
436
Ease of Use
8.5
22
8.2
443
Ease of Setup
8.1
12
8.2
308
Ease of Admin
7.2
12
8.5
160
Quality of Support
8.2
20
9.0
390
Has the product been a good partner in doing business?
8.3
12
9.3
163
Product Direction (% positive)
7.8
21
8.9
432
Features by Category
Not enough data
7.5
263
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
9.0
5
7.3
55
Data Management
8.3
5
8.5
51
8.3
5
8.4
47
8.7
5
8.6
51
9.3
5
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
9.0
5
7.8
50
9.7
5
7.7
47
Monitoring and Management
9.3
5
9.2
55
Not enough data
7.6
48
Cloud Deployment
9.0
5
7.4
43
9.0
5
7.0
41
Generative AI
Not enough data
6.2
34
Not enough data
6.1
34
7.8
19
7.4
341
Functionality
8.2
19
7.4
291
9.0
19
8.8
323
8.1
18
8.1
294
7.8
18
8.0
299
Management
8.2
19
8.7
318
7.6
18
7.7
287
7.9
18
8.3
311
7.2
18
8.0
305
8.4
18
8.1
312
Generative AI
5.8
6
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
Not enough data
7.0
193
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
Bigeye
Bigeye
Monte Carlo
Monte Carlo
Bigeye and Monte Carlo are categorized as DataOps Platforms and Data Observability
Unique Categories
Bigeye
Bigeye has no unique categories
Monte Carlo
Monte Carlo is categorized as Database Monitoring and Data Quality
Reviews
Reviewers' Company Size
Bigeye
Bigeye
Small-Business(50 or fewer emp.)
54.5%
Mid-Market(51-1000 emp.)
27.3%
Enterprise(> 1000 emp.)
18.2%
Monte Carlo
Monte Carlo
Small-Business(50 or fewer emp.)
3.5%
Mid-Market(51-1000 emp.)
45.7%
Enterprise(> 1000 emp.)
50.8%
Reviewers' Industry
Bigeye
Bigeye
Information Technology and Services
22.7%
Computer Software
13.6%
Consulting
4.5%
Sports
4.5%
Online Media
4.5%
Other
50.0%
Monte Carlo
Monte Carlo
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%
Alternatives
Bigeye
Bigeye Alternatives
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Databricks Data Intelligence Platform
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Hightouch
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Boost.space
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Census
Census
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Monte Carlo
Monte Carlo Alternatives
Acceldata
Acceldata
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Anomalo
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Datadog
Datadog
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Soda
Soda
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Discussions
Bigeye
Bigeye Discussions
Monty the Mongoose crying
Bigeye has no discussions with answers
Monte Carlo
Monte Carlo Discussions
What is Monte Carlo software?
1 Comment
Molly V.
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
Monty the Mongoose crying
Monte Carlo has no more discussions with answers