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

Keep Datadog and SingleStore 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 SingleStore

Keep SingleStore and Datadog in step: the rows in your database and the Service Level Objectives, Hosts, Monitors, Logs your engineering tools track stay consistent in real time, in both directions.

SingleStore 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 Reference Tables, Pipelines, Stored Procedures, Indexes and Shard Keys in SingleStore with Service Level Objectives, Hosts, Monitors, Logs 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 data from transactional databases and SaaS apps into one store that handles both lookups and scans.
  • 02 Keep reference data consistent between SingleStore and application databases.
  • 03 Provision and update Datadog Monitors from a config database or Git so alert definitions stay consistent across teams and environments.
  • 04 Publish deploy and pipeline Events, and submit custom Metrics, into Datadog from CI/CD or a data pipeline to enrich dashboards and correlation.

Common sync patterns

Turn rows into the records your tools track

A new or changed row in SingleStore 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 SingleStore as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

One integration pattern instead of per-tool API code

Read and write the synced tables in SingleStore and Stacksync keeps Datadog current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.

What you can sync between Datadog and SingleStore

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 SingleStore 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. Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. Logs is specific to Datadog and Indexes and Shard Keys to SingleStore — 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. Databases The connection target containing the tables a sync addresses. Events is specific to Datadog and Databases to SingleStore — 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 (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. Dashboards is specific to Datadog and Tables (rowstore and columnstore) to SingleStore — 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 Read-only projections used as curated sync sources. Metrics is specific to Datadog and Views to SingleStore — 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. Reference Tables Small tables replicated to every node, often used for dimension data in syncs. Incidents is specific to Datadog and Reference Tables to SingleStore — 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. Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs. Service Level Objectives is specific to Datadog and Pipelines to SingleStore — each maps to any object or custom field on the other side.

How changes propagate between Datadog and SingleStore

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

SingleStore Datadog Interval-based propagation

DetectionStacksync polls SingleStore for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or watermark columns.

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.
  • SingleStore: No API rate limits; throughput is bounded by workspace or cluster size.
What ships with Datadog ⇄ SingleStore

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or SingleStore 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 SingleStore record.

Observability

Monitoring

Track your Datadog ⇄ SingleStore 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 SingleStore.

How the Datadog and SingleStore 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.

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size
How it works

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

    Choose tables

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

Datadog and SingleStore 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 328 integrations available for Datadog and SingleStore.

Popular · 7 of 328
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