What is database monitoring?

Database monitoring is application performance monitoring (APM) tuned for database systems of all types and sizes. Database monitoring gives IT teams the insight they need to proactively make sure databases and the services that use them are optimized for performance, are stable and reliable, and remain secure.

From sales and finance to engineering and manufacturing, modern businesses depend on database management systems to function seamlessly. When these systems slow down, crash, or experience breaches, the consequences ripple across both internal operations and customer-facing processes.

As the backbone of business operations, databases must be fast, reliable, and secure—regardless of where or how they are hosted. Ensuring this is one of the IT team’s most critical responsibilities. To achieve it, IT teams rely on robust database monitoring systems to safeguard performance, maintain reliability, and protect data integrity.

How does database monitoring work & why is it important?

Effective database activity monitoring, like other APM services, tracks critical metrics, analyzes key events, and processes essential logs and traces. What sets database monitoring apart is its ability to evaluate query efficiency—often a major factor behind slow performance. The service consolidates this data alongside other relevant information, providing valuable insights. Through alerts, intelligent analytics, automation, and visually intuitive dashboards, teams across the organization can gain a clear picture of database performance and proactively address potential issues before they affect users.. 

By monitoring and analyzing database performance, teams can:

• Maximize availability by early visibility into resource consumption and contention issues and from proactive alerts.
• Optimize efficiency of queries through query and trace analysis.
• Guarantee resources with visibility into real-time demand impacts and automated provisioning and load-balancing across an entire infrastructure. 
• Protect data integrity and guard against intrusion through security monitoring and detection of suspicious activity.
• Leverage observability and automation tools to maximize team efficiency, allowing more time for critical initiatives.

These benefits enable companies to maximize the best customer experiences, build and retain customer trust, help improve operational efficiencies that impact their revenue generation and bottom line, and allow them to better comply with governance requirements, such as GDPR, HIPPA, and others. 

Key components of an effective database monitoring system

Database monitoring is made up of a combination of several key processes. Each has their own types of data capture and analytics: 

Performance monitoring gathers multiple metrics, including resource utilization (CPUs, memory, network, cache), connection statistics, query performance, user sessions, deadlock details, and system and user errors. When combined with log analysis and traces and visualized in intelligent dashboards, these metrics assemble an accurate picture of database and system performance. Built-in automation tools help IT teams proactively address issues before they reach customers.

Security monitoring focuses on protecting databases from threats, such as SQL injections, unusual and unauthorized access, configuration and schema changes, abnormal query patterns, and others. Data breaches are costly and bad actors are getting more sophisticated. As a result, companies must continually be watchful and vigilant with their database security monitoring services.

Compliance monitoring for databases is a requirement to adhere to strict government and industry regulations. If audits find companies are noncompliant with customer data and transactions, regulatory bodies can effect severe legal and financial penalties. Noncompliance can also create distrust with customers, translating to additional loss of loyalty and revenue. Database compliance monitoring helps ensure lawful handling of customer data, helping avoid penalties and impact on a company’s reputation.

Common challenges in database monitoring and how to overcome them

The exponential acceleration in the volume, variety, and velocity of data that companies now ingest amplifies the challenges to database monitoring. Distributed data systems and data lakes complicate monitoring even further. Here are some challenges to consider.

What to monitor 

Selecting too many metrics, events, logs, and traces—or not enough—can create a negative impact on performance or missing issues. For example, excessive use of profilers, agents, and logging can slow down database performance. Before starting the selecting phase, be sure you understand your end objectives. These will drive what you need to monitor and why.

Data volume and complexity

Companies are taking in more data than ever and finding ways to make use of it, which means greater stress on your data management system and monitoring abilities. Looking at your data system architectures with the future and monitoring in mind can help you plan and evolve systems to run more efficiently.

Scalability and performance

As data grows exponentially, so does the need to scale monitoring services and performance, as well as to ensure recoverability. Choose tools and services that can keep up with expected data growth in an efficient manner. 

Technology diversity 

SQL, NoSQL, textual, video and imaging; CPUs, GPUs, and TPUs; general-purpose nodes, large-memory nodes, containers, in-memory databases; data locality. The diversity and distribution of technologies in software and hardware and where data resides creates complexity for monitoring and analysis. Make sure any third-party monitoring services are flexible enough to cover all of your technologies.

Security and Compliance

If you operate in a regulated industry, you have no choice but to institute measures that monitor compliance with your specific regulations. Even if your industry isn’t regulated, personally identifiable information (PII) and customer transaction data you retain will fall under some kind of protection requirement. Your monitoring capabilities must check that you meet whatever rules to which you need to comply.

Alerting and Analysis

Built-in alerts and notifications are typically standard in any monitoring solution. That’s the point of monitoring. On the other hand, intelligent analytics capabilities can vary from one service or solution to another. And AI-powered database monitoring—like AI everywhere—is evolving. Whether your solution is in-house or out-sourced, it should stay current with model retraining and software updates.

Best practices for database monitoring

To maximize the benefits of database monitoring and database performance, consider adopting the following practices as part of your organization’s regular routine:

Monitor key metrics

As with observability practice overall, what you choose to monitor will drive the value of insight you achieve from the tools. At minimum, check resource consumption, contention, and availability; monitor query efficiency and performance; and monitor network and system throughput across your entire data management system stack. 

Analyze logs

Analyzing logs provides context to your metrics and events as they are flagged. Manually reviewing logs is impossible with today’s scaling of data management systems. AI-powered, automated log analysis provides the insight you need and visualizes it in intuitive dashboards. You can easily explore your data, understand context, and resolve problems faster. 

Identify slow queries

Regularly monitor query throughput and performance. Identify slow or inefficient queries and why they create bottlenecks. Optimize queries as needed to accelerate response times. Your monitoring tools should include capabilities to automatically find inefficient queries.

Set up alerts

Set up real-time alerts to instantly respond to the most critical issues. Set up other alerts according to your response policies. If something needs immediate attention, look for automation tools that can address the issue while teams respond to the alert. Monitoring, alerts, and automation go hand-in-hand.

Establish baselines

You’ll never know how you’re improving your database activity monitoring if you don’t set baselines for all monitoring and analytics. Utilize historical data to analyze trends that establish a starting point for metrics, events, logs, and traces. By comparing real-time metrics to baselines, you can begin to identify patterns and potential problems. From there, you can reset your thresholds as your monitoring system learns the ground truth across your data management systems. 

Make security and compliance monitoring a priority

Prioritizing security and compliance sets a standard for your company to commit to the safety of your customer data and compliance with regulations. Breaches and failed audits are costly for any business. 

Looking for more ways to boost database performance? Get more strategic tips for improving database performance in high-traffic environments.