Sold by: Monte Carlo DataÂ
Deployed on AWS
Data breaks. We ensure your team is the first to know and the first to solve with end-to-end data observability.
Overview
As businesses increasingly rely on data to power digital products and drive better decision making, it's mission-critical that this data is accurate and reliable. Monte Carlo's Data Observability Platform is an end-to-end solution for your data stack that monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence. The platform uses machine learning to infer and learn your data, proactively identify data issues, assess its impact, and notify those who need to know. By automatically and immediately identifying the root cause of an issue, teams can easily collaborate and resolve problems faster. Monte Carlo also provides automatic, field-level lineage and centralized data cataloging that allows teams to better understand the accessibility, location, health, and ownership of their data assets, as well as adhere to strict data governance requirements.
Highlights
- Detect: Detect data quality issues before your stakeholders at each stage of the pipeline
- Resolve: Resolve data issues with out-of-the-box root cause and impact analysis, including end-to-end field-level lineage
- Prevent: Prevent data downtime proactively across your stack
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Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months | Overage cost |
|---|---|---|---|
Monte Carlo Credit | Monte Carlo's Data Observability Platform Credit | $50,000.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
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Software as a Service (SaaS)
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Customer reviews
0 ratings
0 AWS reviews
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436 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Financial Services
Great User Interface and Customer Service
Reviewed on Sep 10, 2025
Review provided by G2
What do you like best about the product?
1. Great user interface, straightforward to understand the functions of different section.
2. The customer service is great. Jennifer and Demarcus are really helpful in answering our quesitons and providing suggestions on building what we need.
3. The Monte Carlo integrates well with Teams and Jira.
2. The customer service is great. Jennifer and Demarcus are really helpful in answering our quesitons and providing suggestions on building what we need.
3. The Monte Carlo integrates well with Teams and Jira.
What do you dislike about the product?
1. The methodology of machine learning tools in Monte Carlo could be more straightforward, and it would be great if we can choose the algorithm for machine learning.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps monitor the data quality of tables and reduce our efforts to check the data manually. It makes sure the data goes in and out of our model aligns with our expectations and prevents major data issues happening.
Airlines/Aviation
Quick Wins using Monte Carlo
Reviewed on Sep 02, 2025
Review provided by G2
What do you like best about the product?
Monte Carlo's out of the box monitors create a relatively easy way to set yourself up for some potential big wins. Alerting that your source volume shows a small dip below expectation can potentially uncover a big issue. Focusing on critical data first sets you up to avoid an overwhelming number of alerts as the product 'learns' your data.
What do you dislike about the product?
Monte Carlo is early in the process to support the integration of Data Observability and the supporting Data Pipelines' state.
What problems is the product solving and how is that benefiting you?
Highlights data issues which are not obvious. Provides the capability to allow us to manually create monitors for critical checks. Out of the box monitors means less work to set up the product.
Insurance
Great data observability with easy to use tool
Reviewed on Sep 01, 2025
Review provided by G2
What do you like best about the product?
I've found Monte Carlo straight forward to use and easy to implement. The team at Monte Carlo has been very helpful when we've been onboarding new data products and provide timely and effective feedback for new users.
Despite being a large financial institution, we've been able to integrate MC to our systems using the OOTB supported methods which has made it much more efficient than other third-party products.
The OOTB ML monitoring has been a real hit at my organization and has enabled us to identify a number of issues more quickly than we would have been able to previously.
I've also been impressed by the variety and number of new features that Monte Carlo are releasing which have been especially helpful with incident notification to Teams.
Despite being a large financial institution, we've been able to integrate MC to our systems using the OOTB supported methods which has made it much more efficient than other third-party products.
The OOTB ML monitoring has been a real hit at my organization and has enabled us to identify a number of issues more quickly than we would have been able to previously.
I've also been impressed by the variety and number of new features that Monte Carlo are releasing which have been especially helpful with incident notification to Teams.
What do you dislike about the product?
Some of the documentation around the API's could do with improving and the number of API's make it a little difficult to understand which API to use in which circumstance.
What problems is the product solving and how is that benefiting you?
We implemented MC to allow our data teams to more quickly understand if something was broken and a starting place for the investigation to fix it. This has meant that time to detection and time to recovery are now quicker than before. As part of our financial regulations, we need to provide a level of data quality across all of our core data products, and we were able to map MC's OOTB ML and other monitors to these requirements and provide our regulator with assurance that we are doing this.
Thomas H.
MC is excellent for autonomous asset monitoring
Reviewed on Aug 22, 2025
Review provided by G2
What do you like best about the product?
I like how scalable it is. We have onboarded our first wave of users and they have been able to easily create their own monitors. Our orgs overall trust in our data products has grown significantly.
What do you dislike about the product?
Honestly nothing at this time. I think we're still working throwing which assets we NEED to monitor vs which are just "nice to have".
What problems is the product solving and how is that benefiting you?
MC is our autonomous data quality checker. We have deprecated various scheduled Airflow jobs to monitor our datasets since MC just does it better. MC monitors also demonstrate the ability to grow over time and learn the asset better. We have high confidence in our products now and trust that there are no hidden anomalies.
Internet
Montecarlo has helped us have more detailed insights on our data.
Reviewed on Aug 19, 2025
Review provided by G2
What do you like best about the product?
Montecarlos anomoly detection has helped us correct small data discrepencies that we didnt know existed in our pipelines. The integration with our slack has helped us be notified of discrepancies quicker and more efficiently.
What do you dislike about the product?
When making a monitor the default adds all checks instantly, If you ever have to change them you have to go remove all of them and add them one by one.
What problems is the product solving and how is that benefiting you?
Montecarlo is helping make sure that we provide the best possible data to our stakeholders by allowing us to create custom monitors that give us insight into very specific situations.