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Data warehouse ⇄ Developer tools

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

Keep ClickHouse and Datadog 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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Why teams connect ClickHouse and Datadog

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

ClickHouse is the central store where teams keep Tables (MergeTree family), Databases, Views, Materialized views 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 Events, Dashboards, Metrics, Incidents produced in Datadog are exactly what analysts want to measure in ClickHouse, and the curated rows in ClickHouse 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 (MergeTree family), Databases, Views, Materialized views in ClickHouse with Events, Dashboards, Metrics, Incidents 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 Land product event data alongside synced CRM accounts so analysts join usage and revenue in one place.
  • 02 Sync aggregated ClickHouse query results back into operational tools, such as account-level usage metrics into a CRM.
  • 03 Publish deploy and pipeline Events, and submit custom Metrics, into Datadog from CI/CD or a data pipeline to enrich dashboards and correlation.
  • 04 Load Events and Incidents into a warehouse to correlate deploys, alerts, and outages on one timeline for post-incident review.

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 ClickHouse — and can be provisioned back from it — so ownership and permissions match across both.

What you can sync between ClickHouse and Datadog

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.

ClickHouse objects Datadog objects How this pairing syncs
Distributed tables Query-routing tables over cluster shards in self-managed deployments. 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. Distributed tables is specific to ClickHouse and Metrics to Datadog — each maps to any object or custom field on the other side.
Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. 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. Dictionaries is specific to ClickHouse and Incidents to Datadog — each maps to any object or custom field on the other side.
Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. 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. Tables (MergeTree family) is specific to ClickHouse and Service Level Objectives to Datadog — each maps to any object or custom field on the other side.
Databases Namespaces that group tables and scope permissions for sync users. 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. Databases is specific to ClickHouse and Hosts to Datadog — each maps to any object or custom field on the other side.
Views Saved queries used as curated, read-only sync sources. 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. Views is specific to ClickHouse and Monitors to Datadog — each maps to any object or custom field on the other side.
Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. 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. Materialized views is specific to ClickHouse and Logs to Datadog — each maps to any object or custom field on the other side.

How changes propagate between ClickHouse and Datadog

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.

ClickHouse Datadog Interval-based propagation

DetectionStacksync polls ClickHouse for changes on an incremental schedule, reading only records changed since the previous pass. No log-based CDC for consumers.

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

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

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 ClickHouse ⇄ Datadog

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever ClickHouse or Datadog 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 ClickHouse or Datadog record.

Observability

Monitoring

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

Trading partners

EDI

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

How the ClickHouse and Datadog connectors work

ClickHouse

Integration surface
Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available
Authentication
Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS
Change detection
No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source
Capabilities
read · write

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.
How it works

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

    Choose tables

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

ClickHouse and Datadog 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 ClickHouse and Datadog.

Popular · 8 of 419
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