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Datadog to MongoDB integration — real-time, two-way sync

Keep Datadog and MongoDB 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 MongoDB

Keep MongoDB and Datadog in step: the rows in your database and the Logs, Events, Dashboards, Metrics your engineering tools track stay consistent in real time, in both directions.

MongoDB 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 Indexes, Views, Change streams, GridFS files in MongoDB with Logs, Events, Dashboards, Metrics 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 Keep a MongoDB-backed product catalog aligned with an ERP's item master in both directions.
  • 02 Consolidate documents from multiple clusters or tenants into a single warehouse-facing store.
  • 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

Where Datadog manages users or groups: keep identity aligned

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

Turn rows into the records your tools track

A new or changed row in MongoDB 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.

Land tool activity as queryable rows

Records and events from Datadog arrive in MongoDB as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

What you can sync between Datadog and MongoDB

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 MongoDB objects How this pairing syncs
Events The event stream (deploys, alerts, comments) searched via the v2 Events endpoint and posted via POST /api/v1/events; used to correlate deploy and incident timelines or to publish deploy and pipeline events into Datadog. Collections The table-like sync unit; each collection maps to a table or object in the paired system. Events is specific to Datadog and Collections to MongoDB — each maps to any object or custom field on the other side.
Dashboards Dashboard definitions and widgets via the v1 Dashboards API with full CRUD; exported for backup and audit, or created and updated programmatically from a source of truth. Documents BSON records created, updated, and deleted during syncs, keyed by _id. Dashboards is specific to Datadog and Documents to MongoDB — each maps to any object or custom field on the other side.
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. Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. Metrics is specific to Datadog and Embedded documents and arrays to MongoDB — 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. Indexes Keep lookups by sync key fast on large collections. Incidents is specific to Datadog and Indexes to MongoDB — 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. Views Read-only aggregation-defined sources for filtered sync datasets. Service Level Objectives is specific to Datadog and Views to MongoDB — 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. Change streams The oplog-backed event feed that powers real-time change capture. Hosts is specific to Datadog and Change streams to MongoDB — each maps to any object or custom field on the other side.

How changes propagate between Datadog and MongoDB

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 MongoDB 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 MongoDB as a row-level write, with types converted between the two schemas.

MongoDB Datadog Sub-second propagation

DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).

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.
What ships with Datadog ⇄ MongoDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or MongoDB 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 MongoDB record.

Observability

Monitoring

Track your Datadog ⇄ MongoDB 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 MongoDB.

How the Datadog and MongoDB 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.

MongoDB

Integration surface
MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
Authentication
Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
Change detection
MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
Capabilities
read · write · CDC
MongoDB setup guide
How it works

How to connect Datadog to MongoDB — 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 MongoDB 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
    MongoDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Datadog and MongoDB 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 ⇄ MongoDB
    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 MongoDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Datadog and MongoDB 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 419 integrations available for Datadog and MongoDB.

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