Let us know how we can help

Sales & Pricing

Speak to a rep about your business needs

Contact Sales

Help & Support

See our product support options

Contact Support

General inquiries and locations

Contact us

Popular destinations

common workflow issues

Does this sound like your week?

These aren’t edge cases. They’re the normal operating conditions for teams running Oracle SQL jobs across multiple tools. Here’s how Control-M handles each one.

LATE DATA

Your 02:00 SQL load started. The source extract arrived at 02:17.

Control-M makes the Oracle SQL job dependent on the required file arrival or upstream transfer instead of a clock alone. The database workload starts only after its prerequisite completes, preventing queries from running against missing or incomplete input.

SQL FAILURE

ORA-00060 stopped the load. Three downstream jobs are still waiting.

Control-M detects the failed database job, prevents dependent jobs from advancing, and exposes the failure in the workflow context. Recovery can rerun the affected workload while preserving downstream dependencies, reducing manual intervention and limiting the failure’s blast radius.

AIRFLOW HANDOFF

Your Airflow DAG finished. The Oracle stored procedure never started.

Control-M coordinates the DAG and Oracle database job in one workflow. When the Airflow execution reaches the required state, Control-M releases the dependent stored procedure automatically — eliminating disconnected schedules, hand-built polling, and manual handoffs between orchestration layers.

CONNECTION FAILURE

Oracle was temporarily unreachable. Your nightly pipeline should not die there.

Oracle connection profiles support a configurable number of connection retries (1–24 attempts after a connection failure) and a connection retry time out (1–300 seconds between each attempt). Control-M can re-establish the database connection while keeping the surrounding workflow coordinated, helping transient connectivity failures recover without prematurely releasing downstream processing or requiring an operator to restart the chain.

SLA RISK

The SQL load is running long. The 06:00 reporting SLA is closing.

Control-M tracks the Oracle job as part of the complete SLA service, not as an isolated database task. Teams can identify delays and jobs threatening timely completion, then troubleshoot the affected workflow before late SQL processing delays downstream business delivery.

INTEGRATION FACTS

Control‑M + Oracle SQL

workload.types

SQL scripts · PL/SQL stored procedures · embedded SQL queries · parameterized SQL scripts · SSIS package execution

trigger.type

file arrival · file transfer completion · Apache Airflow DAG completion · API-driven execution · time schedule · upstream job completion

cross_tool.deps

Apache Airflow DAG · OCI Data Integration job · dbt job · file transfer · REST API call · downstream BI workflow

cloud.platforms

on-premises Oracle Database · Oracle Cloud Infrastructure · Control-M SaaS

error_handling

number of connection retries · connection retry time out · downstream dependency hold · job rerun · failure alerting · SLA delay detection

throughput

high-volume batch SQL · parallel database workloads · configurable concurrent connections · scheduled ETL processing · parameterized batch execution

observability

job execution status · SQL output · execution log · workflow dependency view · SLA service monitoring · historical execution visibility

end-to-end orchestration

One production workflow. Every tool in the stack.

Control-M orchestrates workflows across Oracle SQL, Airflow, OCI Data Integration, dbt, 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: Airflow → Oracle SQL → dbt → analytics handoff
  • Data-aware triggers: file arrival, API event, Airflow completion, upstream job result
View all integrations

Oracle SQL

SQL scripts · stored procedures · embedded queries · parameters · SQL output

Apache Airflow

DAG execution · DAG status tracking · task output · workflow dependencies

OCI Data Integration

data integration execution · status monitoring · pipeline coordination

dbt

job execution · transformation handoff · status-driven dependencies

Control-M MFT

file watching · managed transfer · transfer completion dependencies

REST APIs

API calls · workflow triggers · cross-application handoffs

BI / analytics

downstream dependencies · scheduled delivery · SLA coordination

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 Oracle SQL execution across the full pipeline

Oracle shows what happens inside the database; it does not show whether the complete cross-platform data pipeline will finish successfully. Control-M connects Oracle execution with upstream and downstream workflow context so teams can monitor:

  • Database job execution status

  • SQL and execution output

  • Upstream and downstream dependencies

  • Runtime and historical execution

  • Cross-platform workflow failures

SLA ASSURANCE

Protect delivery SLAs beyond the Oracle job

A successful SQL statement does not guarantee an on-time business outcome. Control-M tracks Oracle processing within the end-to-end service, helping teams identify delays across ingestion, transformation, database execution, and downstream delivery before the workflow misses its SLA:

  • End-to-end SLA monitoring

  • Delay and failure visibility

  • Service-level workflow status

  • Dependency-aware troubleshooting

  • Automated operational alerts

Documentation
Integrating Oracle SQL and Control-M Integrating Oracle SQL and Control-M SaaS

Bring order to complex workflows

Learn how Control-M helps teams orchestrate complex processes with greater visibility, coordination, and control.
Schedule a consultation Start a self guided demo