Datadog unveiled that its Database Monitoring product now observes MongoDB databases.

With this announcement, Datadog Database Monitoring supports the five most popular database types—MongoDB, Postgres, MySQL, SQL Server and Oracle.

Datadog Database Monitoring enables application developers and database administrators to troubleshoot and optimize inefficient queries across database environments. With it, teams can easily understand database load, pinpoint long-running and blocking queries, drill into precise execution details and optimize query performance to help prevent incidents and spiraling database costs.

"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," said Omri Sass, Director of Product Management at Datadog. "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."

Datadog Database Monitoring helps teams:

- Ensure high availability of databases: By providing a comprehensive list of database clusters alongside critical metrics like queries per second, reads and writes per second and replication details, teams can monitor overall cluster performance at a glance, detect potential issues early and take preventative measures.

- Optimize query and database performance: Teams track key query performance metrics—like latency, execution time and volume of data queried—to quickly detect long-running transactions, high-impact blockers and missing indices while receiving proactive recommendations to fix these issues.

- Resolve database and application issues faster: By integrating database monitoring and application performance monitoring, Datadog's unified platform correlates health metrics and distributed traces with query metrics and explain plans in one view in order to accelerate root cause analysis of high latency, leading to faster triage and resolution of issues.

MongoDB is a leading modern document database provider. MongoDB's document model streamlines the process of building data-driven applications with a developer-friendly query language and a flexible data model that is easy to work with and easy to scale. The newly added support for MongoDB by Datadog Database Monitoring makes it easier for joint customers to maximize performance by optimizing deployment and infrastructure allocation, for example, by analyzing resource usage and overlapping workloads to make the most of available resources.

"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," said Will Winn, Senior Director of Partners at MongoDB. "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 Database Monitoring's support for MongoDB is now generally available.