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Datadog Extends Monitoring for Microsoft SQL Server and Microsoft Azure Database Platforms

Datadog announced expanded monitoring for Microsoft SQL Server and Microsoft Azure database platforms.

The announcement builds on Datadog’s Database Monitoring product, which launched in August of last year.

With this expanded support, engineers and database administrators can quickly pinpoint and address database performance issues such as costly and slow queries, incorrect indexes in SQL Server or Azure databases and bottlenecks in their applications.

“We launched Database Monitoring last year because we wanted to help our customers reduce database costs, troubleshoot performance inefficiencies and increase collaboration between engineers and database administrators,” said Omri Sass, group product manager of Application Performance Monitoring at Datadog. “By adding support for SQL Server and Azure database services, Microsoft users are better able to accomplish these goals and discover and implement the right database improvements while saving time communicating and reconciling information.”

“Microsoft Azure SQL Database and SQL Managed Instance are fully managed database services that feature built-in security controls, automated maintenance and are always up to date,” said Ramnik Gulati, senior director, product marketing, data & AI at Microsoft. “The expanded support of Datadog’s Database Monitoring product further strengthens this collaboration by providing Microsoft customers with deep insights into their managed and self-hosted SQL Server, PostgreSQL and MySQL databases, enabling them to build and scale workloads with confidence.”

Datadog Database Monitoring for Microsoft SQL Server and Azure database platforms includes the following features:

- Valuable Query Metrics: View metrics such as average latency, total execution time and number of rows queried in order to identify problematic queries and use historical query performance data to track long-term trends.

- Explain Plan Analysis: Visualize differences between multiple explain plans for individual queries to identify hotspots and seamlessly pivot from explain plans to related metrics in order to understand how inefficiencies impact performance.

- Centralized Query, Database and Infrastructure Metrics: View and monitor query-level and host-level metrics together to better understand how resource constraints affect database performance

Database Monitoring is now generally available for Microsoft customers using SQL Server or Azure Database Platforms.

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Datadog Extends Monitoring for Microsoft SQL Server and Microsoft Azure Database Platforms

Datadog announced expanded monitoring for Microsoft SQL Server and Microsoft Azure database platforms.

The announcement builds on Datadog’s Database Monitoring product, which launched in August of last year.

With this expanded support, engineers and database administrators can quickly pinpoint and address database performance issues such as costly and slow queries, incorrect indexes in SQL Server or Azure databases and bottlenecks in their applications.

“We launched Database Monitoring last year because we wanted to help our customers reduce database costs, troubleshoot performance inefficiencies and increase collaboration between engineers and database administrators,” said Omri Sass, group product manager of Application Performance Monitoring at Datadog. “By adding support for SQL Server and Azure database services, Microsoft users are better able to accomplish these goals and discover and implement the right database improvements while saving time communicating and reconciling information.”

“Microsoft Azure SQL Database and SQL Managed Instance are fully managed database services that feature built-in security controls, automated maintenance and are always up to date,” said Ramnik Gulati, senior director, product marketing, data & AI at Microsoft. “The expanded support of Datadog’s Database Monitoring product further strengthens this collaboration by providing Microsoft customers with deep insights into their managed and self-hosted SQL Server, PostgreSQL and MySQL databases, enabling them to build and scale workloads with confidence.”

Datadog Database Monitoring for Microsoft SQL Server and Azure database platforms includes the following features:

- Valuable Query Metrics: View metrics such as average latency, total execution time and number of rows queried in order to identify problematic queries and use historical query performance data to track long-term trends.

- Explain Plan Analysis: Visualize differences between multiple explain plans for individual queries to identify hotspots and seamlessly pivot from explain plans to related metrics in order to understand how inefficiencies impact performance.

- Centralized Query, Database and Infrastructure Metrics: View and monitor query-level and host-level metrics together to better understand how resource constraints affect database performance

Database Monitoring is now generally available for Microsoft customers using SQL Server or Azure Database Platforms.

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2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

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