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Developer tools ⇄ Data warehouse

Datadog to Starburst Enterprise integration — real-time, two-way sync

Keep Datadog and Starburst Enterprise 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 Starburst Enterprise

Close the gap between analytics and operations: Starburst Enterprise holds the record while Datadog runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.

Starburst Enterprise is the central store where teams keep Tables, Views, Materialized views, Columns for reporting and analysis; Datadog runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Hosts, Monitors, Logs, Events produced in Datadog are exactly what analysts want to measure in Starburst Enterprise, and the curated rows in Starburst Enterprise are what should drive the next action in Datadog. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.

Stacksync syncs Tables, Views, Materialized views, Columns in Starburst Enterprise with Hosts, Monitors, Logs, Events in Datadog field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.

Common use cases

  • 01 Write curated or reconciled results back to lakehouse tables through connectors that support inserts
  • 02 Read federated views that join warehouse, lake, and database tables, then sync the result into operational tools like a CRM
  • 03 Sync Monitors and their alert state into Postgres so reliability teams query alert history and noisy-monitor trends in SQL.
  • 04 Provision and update Datadog Monitors from a config database or Git so alert definitions stay consistent across teams and environments.

Common sync patterns

No batch jobs to babysit

New and changed records move field by field the moment they change, replacing scheduled ETL and one-off scripts that fail quietly and leave stale rows behind.

One shared record, kept consistent

Where both systems track the same entity, a change on either side propagates to the other, ending the manual reconciliation between the operational copy and the warehouse copy.

Keep user and access records aligned

Where Datadog manages users, directory, or access data, those records stay current in Starburst Enterprise — and can be provisioned back from it — so ownership and permissions match across both.

What you can sync between Datadog and Starburst Enterprise

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 Starburst Enterprise objects How this pairing syncs
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. Catalogs Each catalog maps to a connector (Iceberg, Hive, PostgreSQL, and others) exposing an external source. Logs is specific to Datadog and Catalogs to Starburst Enterprise — each maps to any object or custom field on the other side.
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. Schemas Namespaces within a catalog, mirroring the underlying source's databases or schemas. Events is specific to Datadog and Schemas to Starburst Enterprise — 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. Tables Queryable relations; writes pass through to sources whose connectors support them. Dashboards is specific to Datadog and Tables to Starburst Enterprise — 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. Views Engine-level SQL views used to shape federated data before syncing it out. Metrics is specific to Datadog and Views to Starburst Enterprise — 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. Materialized views Precomputed results that make repeated sync reads cheaper. Incidents is specific to Datadog and Materialized views to Starburst Enterprise — 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 Typed per the Trino type system, mapped from each source's native types. Service Level Objectives is specific to Datadog and Columns to Starburst Enterprise — each maps to any object or custom field on the other side.

How changes propagate between Datadog and Starburst Enterprise

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

Starburst Enterprise Datadog Interval-based propagation

DetectionStacksync polls Starburst Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling.

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.
  • Starburst Enterprise: Throughput is governed by cluster sizing and resource groups rather than API quotas.
What ships with Datadog ⇄ Starburst Enterprise

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or Starburst Enterprise 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 Starburst Enterprise record.

Observability

Monitoring

Track your Datadog ⇄ Starburst Enterprise 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 Starburst Enterprise.

How the Datadog and Starburst Enterprise 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.

Starburst Enterprise

Integration surface
ANSI SQL over JDBC/ODBC drivers and the Trino client REST protocol
Authentication
Deployment-dependent: username/password, LDAP, OAuth 2.0, or Kerberos
Change detection
Query-based polling; Starburst is a query engine and exposes no change log of its own
Capabilities
read · write
Rate limits
Throughput is governed by cluster sizing and resource groups rather than API quotas
How it works

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

    Choose tables

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

Datadog and Starburst Enterprise 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.

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:

Related integrations

Every pair below is a real-time, two-way sync. Search all 315 integrations available for Datadog and Starburst Enterprise.

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