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Control-M + Fivetran
Your data pipeline starts before Fivetran runs — and fails when something upstream breaks.. A source extract arrives late. A schema changes unexpectedly. A downstream warehouse isn’t ready. Control-M orchestrates the full chain: ingestion, synchronization, transformation, validation, and delivery.
common workflow issues
Does this sound like your week?
These aren’t edge cases. They’re the normal operating conditions for teams running Fivetran syncs across multiple tools. Here’s how Control‑M handles each one.
SYNC DEPENDENCIES
2:00 AM sync finished. The warehouse load never started.
Fivetran completes successfully, but downstream processes still depend on manual triggers or polling. Control-M detects sync completion events, validates prerequisites, and launches dependent jobs automatically, eliminating delays between ingestion and processing.
SCHEMA CHANGES
A source column changed. Three downstream jobs failed.
When source systems introduce schema changes, downstream transformations can break unexpectedly. Control-M coordinates validation checkpoints, exception handling, and notification workflows so failures are isolated early and remediation begins before broader pipeline impact occurs.
SLA RISK
The sync ran long. The morning dashboard missed its window.
Control-M continuously tracks execution times and predicts SLA risk before deadlines are missed. Automated alerts, escalation policies, and recovery actions help teams address delays before business users see stale data.
FAILURE RECOVERY
The API quota reset overnight. Half the syncs stopped.
Control-M automates retries based on exit conditions, configurable wait intervals, and dependency logic. Failed syncs can resume without triggering unnecessary downstream jobs, preventing cascading failures across the pipeline.
CROSS-TOOL VISIBILITY
Fivetran succeeded. dbt failed. Nobody saw the connection.
Data teams often troubleshoot across multiple consoles. Control-M provides a unified workflow view spanning Fivetran, dbt, warehouses, and reporting tools, making root-cause identification faster and operational ownership clearer.
INTEGRATION FACTS
Control‑M + Fivetran
|
workload.types |
connection synchronization · re-synchronization · data transformation · connector execution · incremental sync · managed data ingestion |
|
trigger.type |
sync completion event · API call · webhook · file arrival · time schedule · upstream job completion · workflow condition |
|
cross_tool.deps |
dbt Cloud run trigger · Snowflake workload · Databricks job · BigQuery processing · Airflow DAG trigger · REST API workflow · BI refresh |
|
cloud.platforms |
AWS · Microsoft Azure · Google Cloud Platform · SaaS data platforms · hybrid environments |
|
error_handling |
configurable retry count · dependency-based recovery · failure isolation · downstream cascade prevention · SLA alerts · Slack · PagerDuty |
|
throughput |
high-volume data ingestion · incremental replication · bulk synchronization · large-scale ETL processing |
|
observability |
job-level audit log · SLA tracking · dependency lineage visualization · centralized monitoring · Datadog integration |
end-to-end orchestration
One production workflow. Every tool in the stack.
Control-M orchestrates workflows across Fivetran, dbt, Snowflake, Databricks, file transfers, and cloud services in a single job flow — with dependency tracking, SLA visibility, and automated recovery across all of them.
- Cross-tool dependency: Fivetran sync → dbt transformation → Snowflake workload → BI refresh
- Data-aware triggers: file arrival, API event, sync completion, validation result
|
Fivetran |
sync orchestration · completion detection · dependency management |
|
dbt Cloud |
run triggering · status monitoring · conditional execution |
|
Snowflake |
workload execution · task orchestration · SLA tracking |
|
Databricks |
job scheduling · cluster workflow coordination · status visibility |
|
Amazon S3 |
file arrival triggers · ingestion validation · event-based workflows |
|
Apache Airflow |
DAG triggering · status tracking · dependency coordination |
|
Power BI |
refresh orchestration · delivery validation · reporting workflows |
airflow coexistance
Control-M doesn’t replace your Airflow DAGs. It runs the layer above them.
The objection is common: “We’re already on Airflow.” The issue isn’t what Airflow does – it’s what happens before and after Airflow runs. That’s where pipelines actually fail.
Airflow manages its DAG. Control-M manages everything surrounding it.
airflow handles
DAG-level orchestration inside the data pipeline
- DAG-level task orchestration within data pipelines
- Python operators, sensors, and task dependencies
- Execution graph for jobs that run inside your pipeline
- Manages retries within a single DAG context
control-m adds
The coordination layer around your DAGs
- Coordination layer around DAGs — triggers Airflow based on upstream conditions: file arrivals, API events, other tool completions
- Tracks each DAG’s SLA contribution across the full end-to-end workflow, not just its own routine
- Manages failure recovery when upstream dependencies fail before Airflow even starts
- Existing DAGs don’t need to be rewritten or migrated
MONITOR PIPELINES
Monitor Fivetran syncs across your entire data stack.
Fivetran shows synchronization status, but data teams still need visibility into everything before and after ingestion. Control-M provides centralized monitoring across the complete workflow lifecycle:
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Sync execution status
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Runtime history tracking
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Dependency visualization
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Pipeline health indicators
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Cross-platform monitoring
SLA ASSURANCE
Keep downstream analytics on schedule.
Fivetran can complete successfully while downstream delivery still misses business deadlines. Control-M monitors workflow SLAs end-to-end and initiates corrective actions before reporting windows are missed:
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SLA breach prediction
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Automated escalation paths
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Dependency-aware recovery
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Proactive alerting
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Business deadline tracking
Documentation
Bring order to complex workflows
Learn how Control-M helps teams orchestrate complex processes with greater visibility, coordination, and control.
