# What database monitoring software is most trusted by Software Engineers and database administrators, based on user reviews?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">DBAs and engineers, you already know the real test for <a class="a a--md" elv="true" href="https://www.g2.com/categories/database-monitoring">database monitoring software</a>: does the alert fire before a slowdown turns into a full outage, or does it fire right after users start complaining?</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Datadog, Dynatrace, and Monte Carlo lead this list. Rounding it out:</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/datadog/reviews"><strong>Datadog</strong></a><strong>:</strong> 4.4 stars across 726 reviews, integrates infrastructure, application, and log monitoring into one unified, real-time observability platform.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/dynatrace/reviews"><strong>Dynatrace</strong></a><strong>:</strong> 4.5 stars across 1,369 reviews, the largest sample here, uses AI-powered insights to transform digital ecosystem complexity into a manageable business asset.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/monte-carlo/reviews"><strong>Monte Carlo</strong></a><strong>:</strong> 4.3 stars across 547 reviews, consistently ranked #1 in data observability on G2, monitoring data pipelines across four trust dimensions.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/solarwinds-worldwide-llc-solarwinds-observability/reviews"><strong>SolarWinds Observability</strong></a><strong>:</strong> 4.3 stars across 867 reviews, matches Monte Carlo's rating, its AIOps capabilities accelerate issue remediation with predictive anomaly-based alerts.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/site24x7/reviews"><strong>Site24x7</strong></a><strong>:</strong> 4.6 stars across 471 reviews, the highest rating here, monitors end-user experience from more than 100 global locations.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For anyone who's actually lived through a real database incident: did the tool catch it first, or did a user report the problem before the alert ever fired?</p>

##### Post Metadata
- Posted at: 14 days ago
- Author title: Writer
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;The detect-before-users-report question has a technical answer: it depends on what layer the baseline lives at. Host metrics, like CPU and memory, catch outages; what users actually report is slowness, and slowness creeps in at the query level, as a plan regression or an index that stopped fitting, while every infrastructure dashboard stays green. So the differentiating question for this category isn&#39;t alert speed, it&#39;s whether the tool baselines individual query performance and fires on degradation there. Tools that watch the database as a box detect incidents; tools that watch queries detect the month before the incident.&lt;/p&gt;

##### Comment Metadata
- Posted at: 13 days ago
- Author title: Tech Consultant





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