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Datadog to SQL Server integration — real-time, two-way sync

Keep Datadog and SQL Server in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Datadog and SQL Server

Keep SQL Server and Datadog in step: the rows in your database and the Dashboards, Metrics, Incidents, Service Level Objectives your engineering tools track stay consistent in real time, in both directions.

SQL Server is where your application's durable data lives; Datadog is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.

Stacksync syncs Tables, Views, Columns, Primary and Unique Keys in SQL Server with Dashboards, Metrics, Incidents, Service Level Objectives in Datadog field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.

Common use cases

  • 01 Consolidate branch or plant databases into a single operational SQL Server hub
  • 02 Bi-directional sync between SQL Server rows and CRM objects so .NET line-of-business apps and sales tools share one dataset
  • 03 Pull the Hosts inventory into a CMDB or database for asset tracking, tag hygiene, and cost allocation across teams.
  • 04 Sync Monitors and their alert state into Postgres so reliability teams query alert history and noisy-monitor trends in SQL.

Common sync patterns

React to changes on either side in near real time

Updates in Datadog arrive as row changes in SQL Server, and writes to SQL Server propagate to Datadog within seconds, so triggers, jobs, and alerts fire without polling.

Where Datadog manages users or groups: keep identity aligned

Directory and identity records in Datadog stay matched to the users or owners table in SQL Server, so provisioning and de-provisioning flow from one source.

Turn rows into the records your tools track

A new or changed row in SQL Server creates or updates the matching record in Datadog, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.

What you can sync between Datadog and SQL Server

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Datadog objects SQL Server objects How this pairing syncs
Metrics Time-series metrics queried in aggregate windows through the query API and submitted via POST /api/v1/series; individual raw points cannot be extracted beyond retention. Tables The primary sync target; rows map to records in connected systems. Metrics is specific to Datadog and Tables to SQL Server — each maps to any object or custom field on the other side.
Incidents Incident records from the v2 Incidents API with full CRUD, including status and timeline fields; landed in a database for MTTR reporting or created and updated from an external incident workflow. Views Read-side projections used as outbound sync sources. Incidents is specific to Datadog and Views to SQL Server — each maps to any object or custom field on the other side.
Service Level Objectives SLO definitions and status history via the v1 SLO API with full CRUD; read out for reliability and error-budget reporting, or provisioned and updated from a reliability config. Columns Field-level mapping targets with T-SQL types. Service Level Objectives is specific to Datadog and Columns to SQL Server — each maps to any object or custom field on the other side.
Hosts Infrastructure host inventory with tags and metadata from the v1 host list API; loaded into a CMDB or warehouse for asset tracking, and hosts can be muted or unmuted via the API. Primary and Unique Keys Match keys for idempotent upserts and conflict handling. Hosts is specific to Datadog and Primary and Unique Keys to SQL Server — each maps to any object or custom field on the other side.
Monitors Alert definitions with query, thresholds, and current state via the v1 Monitors API, which supports full create, update, and delete; Stacksync reads alert state into a warehouse or provisions and updates monitors from a config source. CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. Monitors is specific to Datadog and CDC Change Tables to SQL Server — each maps to any object or custom field on the other side.
Logs Log events searched via the v2 Logs search endpoint by time window and submittable through the log intake API; commonly streamed to a warehouse for retention beyond Datadog's storage period. Stored Procedures T-SQL logic that can validate or post-process synced rows. Logs is specific to Datadog and Stored Procedures to SQL Server — each maps to any object or custom field on the other side.

How changes propagate between Datadog and SQL Server

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Datadog SQL Server Sub-second propagation

DetectionDatadog notifies Stacksync of record changes through webhook events. Polling with time-windowed search queries on Logs and Events (timestamp cursor).

DeliveryEach detected change is applied to SQL Server as a row-level write, with types converted between the two schemas.

SQL Server Datadog Sub-second propagation

DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).

DeliveryEach detected change is written to Datadog through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Datadog: Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.
  • SQL Server: No API rate limits; throughput depends on instance resources, licensing tier, and connection limits.
What ships with Datadog ⇄ SQL Server

Connect Datadog and SQL Server for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Datadog–SQL Server connection.

Real-time

Two-way sync

Changes in Datadog or SQL Server instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or SQL Server data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Datadog or SQL Server record.

Observability

Monitoring

Track your Datadog ⇄ SQL Server sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Datadog and SQL Server.

How the Datadog and SQL Server connectors work

Datadog

Integration surface
REST API (v1 and v2)
Authentication
API key (DD-API-KEY) plus an Application key (DD-APPLICATION-KEY) sent as request headers; application keys are tied to the creating user and inherit that user's permissions and authorization scopes.
Change detection
Polling with time-windowed search queries on Logs and Events (timestamp cursor); monitor alerts can also push via the Webhooks notification integration. No modified-date CDC on mutable objects.
Capabilities
read · write · webhooks
Rate limits
Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.

SQL Server

Integration surface
SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers
Authentication
Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page
Change detection
SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance resources, licensing tier, and connection limits
SQL Server setup guide
How it works

How to connect Datadog to SQL Server — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Datadog and SQL Server with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Datadog connected
    SQL Server connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Datadog and SQL Server objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Datadog ⇄ SQL Server
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Datadog SQL Server
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Datadog and SQL Server integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 418 integrations available for Datadog and SQL Server.

Popular · 8 of 418
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