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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Monitor and optimize Supabase query performance with Datadog Database Monitoring
Kyra Abbu, Sophie Bymark, Ignacio Eguinoa, Marlisa Gashaj, Mike · 2026-05-04 · via Datadog | The Monitor blog

Built on Postgres, Supabase is an open source, all-in-one backend platform for developers who want to ship applications without managing infrastructure. This makes it especially popular with frontend developers and vibe coders who may have little to no database expertise. Datadog’s Supabase integration provides high-level infrastructure metrics, but developers also need query-level visibility to easily diagnose, optimize, and trace performance issues back to their source. Without that visibility, it’s difficult to determine whether slowdowns originate in the service layer or in Postgres itself.

Datadog Database Monitoring (DBM) for Supabase gives developers query-level metrics, explain plans, and optimization recommendations in a single platform. Its setup is agentless and can be completed in one click. After setup, developers can detect regressions, trace slowdowns from the application layer to the database, and act on issues even if they lack deep Postgres expertise.

In this post, we’ll show how Database Monitoring for Supabase helps app developers:

  • Monitor Supabase instances with one click

  • Catch performance regressions as soon as they happen

  • Discover and test optimizations to improve performance

  • Trace application slowdowns to their source in the database

Monitor Supabase instances with one click

When teams are focused on shipping fast, setting up deep database monitoring can seem like a burdensome task that is easy to deprioritize. But without visibility into database activity, regressions can go undetected until users start reporting slowdowns.

DBM for Supabase resolves this problem with a one-click, agentless setup. Traditionally, enabling deep database monitoring requires deploying and managing an agent. With the Supabase Cloud integration, you can enable Database Monitoring directly from within Datadog. Datadog connects directly to your database and immediately surfaces the query-level telemetry data that helps you diagnose database performance issues.

Datadog Integrations page showing the Supabase Cloud configuration panel with fields for account details and Database Monitoring setup.

Catch performance regressions as soon as they happen

Rising query execution times are the clearest signal that database performance is degrading. Page loads that were once quick begin to lag, and longer execution times consume more resources. This in turn leads to blocking and timeouts in your application.

With Recommendations, DBM can automatically detect when a query performance has degraded. It then runs diagnostics to check for variations in workload, traffic, deployments, and schema, giving you a starting point for your investigation. You can also configure monitors to capture regressions based on your own rules.

Discover and test optimizations to improve performance

Identifying a slow query is only part of the problem. Knowing whether to rewrite the query, change the schema, or modify application code requires understanding the impact each option will have on the database overall.

DBM provides built-in recommendations so that developers can act on query insights without having deep Postgres expertise. For each recommendation, DBM identifies where the bottleneck in query performance is coming from and provides a solution to resolve it. For example, for the query regression shown above, the screenshot below shows how DBM points to a long sequential scan as the cause. DBM also recommends adding an index to resolve the issue.

Datadog DBM query details page showing a high-severity long sequential scan recommendation with an index creation suggestion and performance charts.

Trace application slowdowns to their source in the database

When application performance degrades, it’s not always clear whether the root cause is in the service layer or the database. Without a link between application behavior and database performance, developers end up switching between tools to find the culprit. This makes determining the source of an issue especially difficult for app developers without database expertise.

With Datadog Application Performance Monitoring (APM) and DBM, teams can trace performance issues from the application layer to their Supabase database by using end-to-end telemetry data. Starting from an impacted service or endpoint in APM, you can drill into the underlying Supabase queries. From there, DBM provides the query-level metrics and investigation context to identify what changed and why, without requiring you to switch tools.

Datadog APM trace flame graph for a /ship_order endpoint showing a slow database query with options to drill into DBM.

Get started with Database Monitoring for Supabase

Database Monitoring for Supabase gives app developers, regardless of their Postgres experience, the tools to identify, diagnose, and resolve database performance issues. With APM and DBM connected, you can easily trace a slow request from the application layer to the query responsible for any issue. From there, built-in recommendations tell you what to fix to resolve the issue.

To get started, visit the docs on setting up Database Monitoring for Supabase. And if you’re new to Datadog, you can sign up for a 14-day free trial.