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Control-M + SAP/Sybase SQL
Your SAP/Sybase SQL workflow starts before a stored procedure or SQL script ever executes — and it can fail when something upstream breaks. An SAP ASE extract arrives incomplete. An SAP Data Services transformation finishes after its processing window. Control-M orchestrates the full chain: data arrival, upstream transformation, SAP/Sybase SQL execution, and downstream delivery.
common workflow issues
Does this sound like your week?
These aren’t edge cases. They’re the normal operating conditions for teams running SAP/Sybase SQL across multiple tools. Here’s how Control‑M handles each one.
UPSTREAM DELAY
Your 2:00 AM data load slipped. The SQL script still depends on it.
Control-M holds the SAP/Sybase SQL job until its upstream conditions are satisfied, then releases execution automatically. Cross-job dependencies replace disconnected schedules, preventing database processing from starting against data that has not arrived or finished processing.
CONNECTION FAILURE
SAP ASE is temporarily nreachable. Your overnight processing window is shrinking.
Control-M for Databases supports configurable connection retries and retry intervals for database connection profiles. Temporary connectivity failures can be retried automatically instead of immediately breaking the workflow, reducing manual intervention during time-sensitive database processing.
SQL FAILURE
A stored procedure fails. Three downstream analytics jobs are waiting.
Control-M monitors the database job’s completion and keeps dependent jobs from proceeding when the required predecessor has not completed successfully. Teams can inspect execution and SQL output centrally, resolve the failure, and restart processing without manually reconstructing the dependency chain.
SLA RISK
The query is still running at 5:40 AM. Reporting starts at six.
Control-M brings SAP/Sybase SQL processing into the end-to-end service workflow, where database jobs can contribute to SLA tracking and predictive delay detection. Teams see risk before the final reporting deadline is missed instead of discovering it downstream.
OUTPUT VISIBILITY
The job completed. Now someone has to determine what the SQL returned.
Control-M can append execution logs and SQL output directly to database job output, with text, XML, CSV, or HTML formatting. Data teams get execution evidence and query results alongside workflow status instead of switching tools to investigate every run.
INTEGRATION FACTS
Control‑M + SAP/Sybase SQL
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workload.types |
Stored Procedures · SQL Scripts · Embedded Query database jobs · parameterized SQL execution · SAP ASE database jobs |
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trigger.type |
time schedule · upstream job completion · file arrival · Control-M event · API-submitted workflow · dependency condition |
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cross_tool.deps |
Control-M Managed File Transfer · Apache Airflow DAG · Informatica workflow · SAP job · REST API call · downstream analytics job |
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cloud.platforms |
Control-M SaaS · self-hosted Control-M · hybrid environments · remote SAP ASE/Sybase database hosts |
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error_handling |
database connection retries · configurable retry interval · dependency-based cascade prevention · job output capture · SLA monitoring · automated alerting |
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throughput |
concurrent database connections · 1–512 connection limit configuration · scheduled batch processing · parallel independent database jobs · centralized connection profiles |
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observability |
database job status · execution log · SQL output · text/XML/CSV/HTML output · dependency visibility · SLA tracking |
end-to-end orchestration
One production workflow. Every tool in the stack.
Control-M orchestrates workflows across SAP/Sybase SQL, SAP applications, Airflow, Informatica, 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: SAP/Sybase SQL → Airflow DAG → cloud transformation → analytics handoff
- Data-aware triggers: file arrival, API event, upstream job completion, database job completion
|
SAP/Sybase SQL |
Stored Procedure · SQL Script · Embedded Query · SQL output capture |
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SAP applications |
SAP job orchestration · dependency coordination · workflow monitoring |
|
Apache Airflow |
DAG triggering · completion tracking · upstream/downstream coordination |
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Informatica |
workflow orchestration · dependency management · completion tracking |
|
Control-M MFT |
file arrival · managed transfer · downstream job triggering |
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Cloud data services |
cross-cloud orchestration · dependency coordination · workflow monitoring |
|
REST APIs |
API-driven workflow integration · cross-tool 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 DATABASE JOBS
Monitor SAP/Sybase SQL execution in one workflow.
SAP ASE shows what is happening inside the database; it does not show how that execution affects every external pipeline dependency. Control-M adds centralized workflow visibility around SAP/Sybase SQL jobs, including execution evidence and downstream status:
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Database job execution status
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SQL and execution output
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Upstream and downstream dependencies
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End-to-end workflow status
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Centralized failure visibility
SLA ASSURANCE
Keep SAP/Sybase SQL pipelines on schedule.
A successful database call does not guarantee that the business pipeline will finish on time. Control-M connects SAP/Sybase SQL processing to the service deadline, exposing dependencies and emerging delays so teams can intervene before downstream delivery is affected:
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End-to-end SLA tracking
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Predictive delay detection
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Dependency-aware workflow monitoring
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Automated failure alerts
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Centralized service visibility
Documentation
Bring order to complex workflows
Learn how Control-M helps teams orchestrate complex processes with greater visibility, coordination, and control.
