Database Activity Monitoring

As database environments grow more complex, visibility into who accesses what—and when—becomes essential. That’s where database activity monitoring software comes in. These platforms continuously track database operations, logging every query, access attempt, and modification to support security, compliance, and performance goals.

DataSunrise offers a robust solution that simplifies monitoring across hybrid cloud and multi-database systems. Its real-time analytics, flexible rule engine, and alerting mechanisms help organizations stay ahead of threats while meeting regulatory demands.

What Is Database Activity Monitoring?

Database activity monitoring (DAM) refers to the practice of tracking and analyzing database operations in real time. Think of it as a security camera for your data, recording everything from SELECT queries to schema changes and logins—then alerting administrators when something looks off.

Why It Matters

Effective DAM helps:

Prevent unauthorized access and detect suspicious behavior
Fulfill compliance requirements for GDPR, HIPAA, PCI DSS, and more
Pinpoint slow queries and performance bottlenecks
Understand user behavior through data access patterns

Core Features of a DAM System

1. Real-Time Activity Capture

Modern solutions log a wide range of activities, including:

SQL statements
Data modifications (INSERT/UPDATE/DELETE)
Schema changes
Login attempts and session metadata

DataSunrise’s Transactional Trails feature delivers deep insight into every monitored query.

SELECT query audit logs in DataSunrise — Detailed tracking of SELECT queries with timing and result-level granularity.

These logs capture execution times, query text, and can optionally include result sets—making them invaluable for audit and forensic analysis.

Real-time performance view in DataSunrise — Visualize traffic, memory usage, and active queries with DataSunrise’s monitoring dashboard.

2. Alerting and Notifications

When risky activity is detected, DAM tools generate alerts. DataSunrise allows alerts to be delivered via email, Slack, or SIEM systems.

DAM alert rule configuration with subscriber — Assign alert recipients directly in rule setup—ensuring prompt incident response.

3. Persistent Audit Trails

A key role of DAM is maintaining a detailed record of who did what. These logs are essential for investigations, internal audits, and regulatory reviews.

-- PostgreSQL: Sample trigger-based audit log
CREATE TABLE user_activity_log (
  id SERIAL PRIMARY KEY,
  event_time TIMESTAMP DEFAULT current_timestamp,
  username TEXT,
  action TEXT,
  table_accessed TEXT,
  old_data JSONB,
  new_data JSONB
);

CREATE OR REPLACE FUNCTION log_user_activity()
RETURNS TRIGGER AS $$
BEGIN
  INSERT INTO user_activity_log(username, action, table_accessed, old_data, new_data)
  VALUES (
    current_user,
    TG_OP,
    TG_TABLE_NAME,
    row_to_json(OLD),
    row_to_json(NEW)
  );
  RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER audit_sensitive_table
AFTER INSERT OR UPDATE OR DELETE ON customer_data
FOR EACH ROW EXECUTE FUNCTION log_user_activity();

Although useful for small environments, this trigger-based approach can’t scale. Tools like DataSunrise offer richer audit capabilities across multiple platforms.

Audit log viewer interface in DataSunrise — Audit trail viewer in DataSunrise makes historical access and change review fast and intuitive.

4. Query Performance Profiling

In addition to security, DAM supports tuning. Profiling helps detect inefficient queries that impact performance. DataSunrise can track performance in proxy mode—minimizing system overhead while collecting execution metrics.

5. SIEM and Compliance Tool Integration

To maintain full-stack visibility, DAM must integrate with enterprise tools. DataSunrise supports SIEM forwarding and API-based connections to compliance platforms and monitoring dashboards.

Evaluating DAM Software

When choosing a solution, look for:

Real-time query tracking
Customizable alerting and audit rules
Cross-platform support (PostgreSQL, MySQL, MongoDB, etc.)
Integration with your existing infrastructure

DataSunrise meets these needs while also offering pre-built templates, self-learning behavior models, and flexible deployment options (on-prem or cloud).

Native vs Third-Party DAM Approaches

PostgreSQL

pg_stat_statements and pgAudit provide built-in activity and compliance-level auditing, respectively. However, they require manual setup and log parsing, and lack real-time alerting or cross-platform coverage.

MongoDB

MongoDB’s profiler captures slow queries and command usage. Compass, the GUI, adds some visualization. But logging read events and correlation with user roles is limited in native tooling.

Organizations often outgrow these built-in options and turn to solutions like DataSunrise for greater coverage and operational simplicity.

Best Practices for Effective Monitoring

Review logs and alerts regularly
Establish a baseline of normal activity
Apply least-privilege access policies
Encrypt sensitive data in transit and at rest
Update rule sets in response to emerging threats

Conclusion

Database activity monitoring is a critical component of modern database security. Whether the goal is compliance, breach prevention, or performance analysis, DAM delivers visibility that generic monitoring cannot.

Solutions like DataSunrise go beyond logging. They offer actionable insights, real-time detection, and cross-environment compatibility—all from a unified console. By choosing a powerful DAM platform and following best practices, you can reduce risk, maintain uptime, and demonstrate due diligence.

Ready to see it in action? Request a demo and explore how DataSunrise makes DAM both powerful and easy to implement.