Source connector

Datadog connector

Datadog integration for databases, warehouses and BI tools

Infrastructure monitoring, logs, and alerting. Datrise captures Datadog entities such as metrics, monitors, events, logs, dashboards and incidents, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Datadog API v2 authenticates with API key, incremental runs key on time-range query window (`from`/`to` epoch parameters), and Datadog caps calls at No single documented default; event submission is capped at 250,000 events/minute per organization, log and metric submission are explicitly not rate-limited, and every other endpoint enforces its own per-endpoint/per-org limit surfaced via `X-RateLimit-*` response headers.

Of the 6 objects, 3 sync as upserts keyed on the primary key and 3 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `datadog_metrics`) with a schema derived from the Datadog API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Datadog pipeline page, and join the waitlist to get the Datadog connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Datadog data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
metrics	datadog_metrics	Append-only, incremental by timestamp
monitors	datadog_monitors	Upsert by primary key, incremental on updated-at
events	datadog_events	Append-only, incremental by timestamp
logs	datadog_logs	Append-only, incremental by timestamp
dashboards	datadog_dashboards	Upsert by primary key, incremental on updated-at
incidents	datadog_incidents	Upsert by primary key, incremental on updated-at

Datadog API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Datadog API v2
Authentication	API key — Requests authenticate with a `DD-API-KEY` header, and any read/query endpoint additionally requires a second `DD-APPLICATION-KEY` header scoped to a user's permissions.
Pagination	cursor — Most v2 list endpoints (users, logs, etc.) use `page[cursor]`/`page[limit]`, with the Logs Search API defaulting to a `limit` of 50 events per page (max 1,000) and returning a `cursor` value to pass into the next request.
Rate limit	No single documented default; event submission is capped at 250,000 events/minute per organization, log and metric submission are explicitly not rate-limited, and every other endpoint enforces its own per-endpoint/per-org limit surfaced via `X-RateLimit-*` response headers
Incremental cursor	time-range query window (`from`/`to` epoch parameters) — Telemetry endpoints (logs, metrics, events, monitors' state) are pulled by re-querying a moving time window rather than following a single resewable cursor field, since most config resources don't expose a documented `updated_at`.
Webhooks	Yes — Webhooks integration (monitor/alert-triggered HTTP callbacks, not a general data-change webhook)
Bulk export	Yes — Log Archives (continuous export of logs to Amazon S3, Google Cloud Storage, or Azure Blob Storage in rehydratable zipped-JSON format)
Deletes detectable	Yes — the Audit Trail API (`/api/v2/audit/events`) records over 100 event types, including resource-deletion events (e.g., monitor/dashboard/pipeline deleted), but only for a 90-day retention window (3/7/15/30/90-day configurable) unless separately archived

Official API reference

What bites when replicating Datadog

Every read endpoint needs both `DD-API-KEY` and `DD-APPLICATION-KEY`; supplying only the API key (sufficient for write-only submission endpoints) fails with a 403 on queries.
There is no general REST rate limit number published; only event submission (250,000/min/org) has a stated cap, so connectors must read `X-RateLimit-Remaining`/`X-RateLimit-Reset` per endpoint rather than assume one budget.
Audit Trail, the only source of resource-deletion events, retains events for a maximum of 90 days by default, so a connector polling less often than that permanently loses visibility into intervening deletes without a separate archive.
Log Archives (the bulk-export path) only cover Logs; there is no equivalent bulk/archive export for metrics or APM traces, which must be pulled incrementally through the regular query endpoints.

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Popular destinations for Datadog

Choose a destination below to open the ready pipeline page.

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Airtable
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Amazon Athena
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Amazon DynamoDB
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Amazon QuickSight
AWS serverless BI with SPICE and embedded analytics.
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Amazon Redshift
AWS petabyte-scale warehouse with Spectrum.
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Amazon S3 Data Lake
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Apache Superset
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Azure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
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Azure Synapse
Microsoft analytics workspace with SQL pools.
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Datadog connector FAQ

What Datadog data does the connector extract?: 6 objects: metrics, monitors, events, logs, dashboards and incidents. Each lands in its own table with types preserved; history-style objects (3: metrics, events and logs) load as append-only streams.
Is the Datadog integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Datadog data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Datadog → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Datadog pipeline with guided onboarding

Join the waitlist to get priority access for Datadog integrations with guided setup, schema-aware mapping, and production-grade incremental sync.