I like that Monte Carlo is integrated with AI, which I find really useful. It's great that it can automatically suggest adding tables, monitors, and setting alerts, plus recommending which alert tables might be missing. This AI-driven feature is very helpful to me. I also recently noticed the Agent preview feature, which allows me to ask simple questions in English, like about tables that are consuming more resources. This eliminates the need to manually query databases for these stats, improving our data warehouse efficiency through cost, read, and write optimizations. Additionally, I find Monte Carlo very user-friendly. Anyone can learn the features and explore them easily, typically within a couple of days. The documentation and videos are readily accessible, making the initial setup very straightforward. Review collected by and hosted on G2.com.

I see some features, maybe missing when working in a big query, like with projects on Google Cloud provider. I'd like Monte Carlo to have integration with Google buckets. It would be helpful if I could set alerts for files not landing on time or if empty files land in the bucket location. Currently, I have to use Python scripts to manage this, and if Monte Carlo had this feature directly, it would be very cool. I have a workaround by creating an external table on top of these buckets and adding it to the ingestion, but direct integration would be much better. Review collected by and hosted on G2.com.

I like the automatic thresholds in Monte Carlo's monitors, which makes it easier not to worry about setting dynamic or fixed thresholds thanks to the automatic ML threshold feature. I also appreciate its integration with orchestration tools like Airflow and DBT, as this allows us to check on specific failures in our workflows. These features help solve our observability issues related to data quality. Review collected by and hosted on G2.com.

Monte Carlo is a great tool but it is very overwhelming. Recently, there have been a lot of changes that affect our processes, like API endpoints, UI, contract, and monitor settings. These changes make us work too much, and they don't share these changes ahead of time. I also don't like that Monte Carlo doesn't allow running SQL queries if the table is not enabled for monitoring. There are some tables we need in queries but don't need the default monitors. The initial setup was quite easy 4 years ago, but now it's not that easy. Alerts are very noisy, and it would be helpful to have a dashboard view to manage these alerts. Review collected by and hosted on G2.com.

The Slack integration is what I like most. I appreciate that I can get alerts directly in Slack and use them to troubleshoot issues quickly. Review collected by and hosted on G2.com.

The fact you cannot customise alerts thresholds with the provided monitors and need to create custom ones for that Review collected by and hosted on G2.com.

Monte Carlo is easy to set up and use. Its automated monitoring, troubleshooting agent, data lineage, and alerting make it easy to detect and troubleshoot data quality issues quickly, helping teams maintain confidence in their data. Review collected by and hosted on G2.com.

Monte Carlo can be expensive, especially as usage scales. One of the downsides of the tool is it cannot validate data after it is offloaded from Snowflake, which limits end-to-end data quality monitoring across the full pipeline. Review collected by and hosted on G2.com.

Monte Carlo Delivers, user friendly solution for the observability. I tac be used both from UI and MaC, which is big advantage. The UI is sometimes slow. AI agents takes pretty much time when there is many monitors in the domain. Technical support is fast, direct support from Laura is very satisfying. She has deep technical knowledge with quick rising up and stepping into issue resolution. Review collected by and hosted on G2.com.

Loading time, UI performance, the timing for AI agents when domain contains many monitors. Review collected by and hosted on G2.com.

I appreciate the investigation query section in Monte Carlo, which is particularly helpful for running additional checks to identify the root cause of issues. I like the data product section where I can see all the monitors I've set up for a particular project. It automates a lot of our validation processes, making it easier to manage and analyze data. Review collected by and hosted on G2.com.

Every time I'm setting up a new monitor, I have to click the test button a couple of times because it says it failed. Eventually, it will pass, but it's quite laggy and a little annoying to deal with. Initially, it took some time for me to understand and get used to because I needed to understand capabilities, the different user roles, and how to find tables. Review collected by and hosted on G2.com.

Good features, easy integrations with Slack/PagerDuty/Jira/etc.

The ui is good, the design also looks good. Review collected by and hosted on G2.com.

There are other ways we can use to to receive alerts and I would say that you need more stuff to differentiate yourself.

I dislike the assets search but the biggest issue for me is that the jobs visualisations are terrible. If a failling happens fast, the bar will be so small I cant even click on that. Also, would be much better if I could filtered based on error instead of looking to all the 1000s models we have hourly/daily. Review collected by and hosted on G2.com.

MC tracks historical metrics for us well, has pretty simple integration with snowflake and consumes not a lot of credits. Review collected by and hosted on G2.com.

it's not that easy to find connection between domains and monitors

default monitor doesn't capture column stats for the added tables

it doesn't have visual graphs in slack messages

it adds entire schema by default which can add 10s-100s of table without noticing and bring bill high Review collected by and hosted on G2.com.

The way of interacting with databases and reviewing potential errors. Also, I appreciate being able to connect Claude to it, to speed up monitor creation and fixing. Review collected by and hosted on G2.com.

I might get lost when there are too many monitors. Review collected by and hosted on G2.com.

Support team is great and very helpful. Threshold can be determined by machine learning, SDK is easy to use for developers. AI features are kept adding to the product. Review collected by and hosted on G2.com.

Some API's document is not very detailed. When new feature roll out, it's not working for the first time. Review collected by and hosted on G2.com.