Monte Carlo Recognized as the #1 Leader in Data Observability and Data Quality by G2

As we turn the corner into 2025, we’re excited to announce that for the 7th quarter in a row, Monte Carlo has been named G2’s #1 Data Observability Platform, as well as #1 in the Data Quality category. This recognition never gets old because G2 bases their rankings on feedback and insights from real customers who work in these tools every day to add value to their business. 

Knowing our products are helping our customers achieve their data goals means everything to us. We’ve always focused on delivering exceptional customer success and improving data quality across the entire data stack — and it’s rewarding to know that hard work continues to translate to meaningful outcomes for our customers.

In the Winter 2025 awards, we were recognized as #1 across the entire Data Observability, Data Quality, and Database Monitoring categories, as well as #1 in the Enterprise Relationship Index. All told, we’re featured in 71 reports, including the #1 spot in 31 reports, and we received 44 badges, including eight Leader badges!

Thanks to each and every customer who left a rating or review. In return, we’ll keep delivering our pledge to continually invest in improving our customers’ data quality and user experiences. 

Over the last few months, that’s meant adding valuable new features and integrations that improve our customers’ visibility into data health and help prevent data quality incidents, including:

• Expanded Databricks and Gitlab integrations to identify query code changes and pull requests that would otherwise result in data quality incidents.
• New observability features for Azure Data Factory, Informatica, and Databricks workflows that help users gain visibility into pipeline failures, lineage, and pipeline performance within a single pane of glass. 

And since generative AI is at the top of mind for our customers (and their CEOs and boards), we continue to look for ways to help organizations improve AI-readiness. Over the last quarter, that’s included sharing resources like our co-founder and CEO Barr Moses’s insights on preparing AI-ready data, data leader Surekha Durvasula’s tips on achieving trusted data at scale, and looking ahead with Tomasz Tunguz to the data and AI trends we anticipate for 2025.

We’ve also been delighted to share stories of how our customers are leveraging their high-quality data to power AI products. For example, the team at Skyscanner uses Monte Carlo to spot data quality issues in their ML training data. As Principal Software Engineer JM Laplante describes, “We have bespoke code that will identify hallucinations or undesirable outcomes in the outputs of a large language model. We can set thresholds in Monte Carlo and then use the alerting and UI to declare incidents in our LLM outputs.”

Data observability also supports advanced data platform development, such as the team at Roche relying on Monte Carlo to ensure data quality while building out a distributed data mesh architecture. “Data observability has really shown its value for us — on one hand, scaling our products, while on the other, keeping them healthy and keeping oversight,” says Data Engineer Hendrik Serryus. 

We have to recognize that all of these outcomes are made possible because of our own incredible team — so we were also honored to be certified as a Most Loved Workplace® and named to America’s Top Most Loved Workplaces list in Newsweek for 2024. 

Together, we’re celebrating 31 #1 G2 awards, including:  

1. Leader in Data Observability
2. Leader in Data Quality
3. Leader in Database Monitoring
4. Leader in Enterprise Data Quality
5. Leader in Enterprise Data Observability
6. Leader in Enterprise Database Monitoring
7. Leader in Relationship for Data Quality 
8. Leader in Enterprise Relationship for Data Quality
9. Leader in Enterprise Relationship for Database Monitoring
10. Leader in Enterprise Relationship for Data Observability
11. Leader in Mid-Market for Data Observability 
12. Leader in Mid-Market for Database Monitoring
13. Leader in Mid-Market for Data Quality
14. Leader in Mid-Market Relationship for Database Monitoring
15. Leader in Mid-Market Relationship for Data Quality
16. Leader in Mid-Market Usability for Data Quality
17. Leader in Mid-Market Implementation for Data Quality
18. Leader in Mid-Market Relationship for Data Quality
19. Leader in Enterprise Europe for Database Monitoring
20. Leader in Enterprise EMEA for Database Monitoring
21. Leader in Europe for Data Quality 
22. Leader in Europe for DataOps
23. Leader in EMEA for Data Quality
24. Leader in EMEA for Database Monitoring
25. Leader in EMEA for DataOps
26. Leader in EMEA for Data Quality
27. Leader in Mid-Market EMEA for Database Monitoring
28. Leader in Mid-Market Europe for Database Monitoring
29. Leader in India for Data Observability
30. Leader in Asia for Data Observability
31. Leader in Asia Pacific for Data Observability

Of course, you don’t have to take our word for it. Here’s what our customers have to say about Monte Carlo: 

If you’d like to learn more about how data observability improves data reliability and supports AI readiness across the entire data and AI stack, get in touch with me or anyone on the rest of the Monte Carlo team!

Our promise: we will show you the product.