Sold by: Monte Carlo Data
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.
4.3
Overview
As businesses increasingly rely on data and AI to power digital products and drive better decision making, it's mission-critical that this data is accurate and reliable. Monte Carlo's Data + AI 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, business intelligence, and AI tools. 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
Details
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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 |
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All fees are non-cancellable and non-refundable except as required by law.
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Delivery details
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Updated weekly
By Monte Carlo Data
By Collibra
Top
10
In Data Governance
Top
10
In Data Catalogs, Data Governance
Top
10
In Data Catalogs, Data Governance
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Quality Monitoring
Machine learning-based monitoring and alerting for data quality issues across data warehouses, data lakes, ETL pipelines, business intelligence, and AI tools
Root Cause Analysis
Automatic root cause identification and impact assessment with end-to-end field-level lineage for data issues
Proactive Issue Detection
Proactive identification of data issues across the data stack before stakeholder notification
Data Lineage and Cataloging
Automatic field-level lineage tracking and centralized data cataloging for data asset accessibility, location, health, and ownership
Multi-Stack Integration
End-to-end observability platform supporting data warehouses, data lakes, ETL systems, business intelligence tools, and AI applications
AI Governance Framework
Active metadata-based governance with rules, processes and responsibilities to ensure ethical AI practices, mitigate risk, adhere to legal requirements, and protect privacy
Automated Data Lineage
End-to-end lineage tracking providing transparency into data transformation and flow across systems, including both summary-level business lineage and detailed technical lineage
Unified Data Catalog
Multi-cloud and hybrid environment data discovery with business context including data origin, ownership, usage patterns, and access to reports, AI models and data products
Data Quality Automation
Automated monitoring and rule management system for enterprise-wide data quality management replacing manual processes
Privacy and Compliance Workflow
Centralized automation of privacy workflows to operationalize privacy requirements and address global regulatory compliance
Data Asset Discovery and Search
Powerful search algorithms combined with browsing capabilities to make data assets including tables, views, BI dashboards, SQL snippets, pipelines, and business metrics instantly discoverable.
Automated Data Lineage Construction
Automatic parsing of SQL query history to construct data lineage and detect personally identifiable information (PII) data for dynamic access policy creation.
Data Quality Profiling
Automatic generation of data quality profiles with variable type detection, frequency distribution analysis, missing values identification, and outlier detection capabilities.
Multi-Platform Integration
Deep integrations with popular data tools including Snowflake, Redshift, Databricks, Looker, and Power BI to create a unified metadata workspace.
Data Governance and Access Management
Automated governance capabilities including PII detection and creation of dynamic access policies for managing data ecosystem permissions.
Standard contract
No
No
Customer reviews
Entertainment
Wide Integration Options and Support for Many Monitoring Use Cases
Reviewed on May 04, 2026
Review provided by G2
What do you like best about the product?
The various integration and scope of different monitors / use cases it supports.
What do you dislike about the product?
Breaking changes have sometimes been an issue for us. Would like there to be more customization around UI / front end and reporting on usage.
What problems is the product solving and how is that benefiting you?
MC is helping us keep our data pipelines healthy and running.
Computer & Network Security
Simple UI and Easy Integrations, but Some Tasks Feel Redundant with Agents
Reviewed on May 04, 2026
Review provided by G2
What do you like best about the product?
ease of use, the ui is simple, and integrations easy
What do you dislike about the product?
things are now can easily done using agents some its making things more redundant
What problems is the product solving and how is that benefiting you?
Monte Carlo provides end-to-end observability. It automatically monitors data stack to alert you when something breaks before a stakeholder reports it.
Akshat S.
AI-Powered Data Monitoring with Seamless Integration
Reviewed on May 02, 2026
Review provided by G2
What do you like best about the product?
I use Monte Carlo for data freshness and custom SQL monitoring. It helps me reliably track my assets' health status in case of any data quality issues or data ingestion delays. I like the troubleshooting agent using AI, which helps debug anomalies in data. I also appreciate the integration with other platforms like Airflow for failure updates. It's also easy to set up with credentials.
What do you dislike about the product?
The free operating agent is not up to the standards of the troubleshooting agent, which has a limit. The alert summary and advice are usually repetitive of the alert description and don’t carry any new information.
What problems is the product solving and how is that benefiting you?
I use Monte Carlo to reliably track my assets' health status in case of any data quality issues or data ingestion delays.
Business Supplies and Equipment
Helpful Tool on Data Observability and Linage, but Maturity Needs uplift
Reviewed on May 01, 2026
Review provided by G2
What do you like best about the product?
Lineage dagram to understand the upstream and downstream relationship.
What do you dislike about the product?
Maturity. Fix one and broke two can surprise end users and shake confidence.
What problems is the product solving and how is that benefiting you?
monitoring snowflake DBs, tables, views, etc, at the schema level, column level, etc.
Shreye S.
Monte Carlo: One-Stop Observability Across Our Entire Data Stack
Reviewed on Apr 30, 2026
Review provided by G2
What do you like best about the product?
Obervability in Monte Carlo oversees our whole data stack. No disparate solutions for different problems - Monte Carlo is our one stop shop for observability.
What do you dislike about the product?
There are a LOT of features, it's easy to get overwhelmed at first.
What problems is the product solving and how is that benefiting you?
Monte Carlo solves the problem of getting visibility into our data pipelines, agentic workflows, and managing uptime of key reports. A single tool for our entire data org's health metrics is a compelling proposition.