Datadog expands database monitoring to support MongoDB

Datadog has expanded its Database Monitoring platform to include MongoDB database observability.

The addition of MongoDB to Datadog's monitoring capabilities means it now supports the top five database types, alongside Postgres, MySQL, SQL Server, and Oracle.

Datadog's Director of Product Management, Omri Sass, explained the importance of this development: "With support for the top five database types in the industry, Datadog Database Monitoring gives teams complete visibility into their databases, queries and clusters so that they can maintain performant databases and tie them to the health of their applications and success of their businesses."

Traditional monitoring tools often limit organisations to monitor either databases or applications.

This can lead to inefficiencies in troubleshooting, prolonged downtimes, and compromised customer experiences. Datadog Database Monitoring offers a solution by allowing application developers and database administrators to monitor inefficient queries consistently and efficiently across various database environments.

The tool provides insights into database loads, identifies long-running and blocking queries, and offers specific execution details to optimise database and query performance, helping prevent costly incidents.

Omri Sass emphasised the critical nature of high availability across database clusters: "Replication failures or misconfigurations can result in significant downtime and data inconsistencies for companies, which may impact their application performance and reliability."

"That's why maintaining high availability across clusters with multiple nodes and replicas is critical."

Datadog Database Monitoring aims to ensure high availability by offering comprehensive data on clusters and critical metrics, such as queries per second and replication details.

This allows users to detect possible issues proactively and take preventative actions.

The platform also optimises query and database performance by tracking key performance metrics like latency and execution time. These insights can help detect long transactions and missing indices, providing recommendations to resolve such issues.

By integrating database and application performance metrics, Datadog accelerates root cause analysis, contributing to faster issue resolution.

With MongoDB's modern document model, the new support from Datadog aids users in optimising their deployments by analysing resource usage more effectively.

Will Winn, Senior Director of Partners at MongoDB, commented on the integration: "As enterprises take advantage of today's increasingly data-intensive workloads, it's critical that they have the tools needed to deploy high-performing applications with complete confidence.

Customers trust MongoDB for its superior performance and flexibility, and now that Datadog Database Monitoring supports MongoDB, ensuring high availability and seamless performance of MongoDB database clusters is even easier."

Datadog's addition of MongoDB monitoring is now available to users.

The development underpins the commitment to enhance database performance and operational efficiency across various platforms, addressing the complex needs of businesses managing data-intensive workloads.