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What is Control-M?

Control-M is a Workload Automation and orchestration platform designed to integrate applications, Data Pipelines, and infrastructure processes. The solution manages Hybrid Cloud (integrated on-premises and cloud resources) environments by providing a framework for the design, automation, and governance of workflows. According to the vendor, the platform is intended to centralize the management of operational dependencies to support organizational compliance and operational efficiency. The solution provides a shared environment for development, data, and operations teams to coordinate Workloads spanning Mainframe systems, cloud applications, and data technologies. This centralized approach is designed to provide visibility into automated processes and replace manual task coordination. Control-M includes monitoring tools intended to identify potential disruptions during process execution to maintain persistent operations. The platform utilizes Predictive Analytics and Event-Driven Automation to identify performance bottlenecks and respond to changing system conditions. The developer states that these capabilities allow operations teams to manage Service Level Agreements (SLAs) and resolve incidents with reduced manual intervention. Control-M integrates with DevOps (Development and Operations) and DataOps workflows to automate software delivery and data management. Organizations in the finance, healthcare, manufacturing, and telecommunications sectors utilize Control-M for tasks requiring high reliability and regulatory compliance. The platform is designed to consolidate fragmented operational environments into structured execution systems. The vendor states that the solution is intended to reduce technical complexity and support organizational agility through automated lifecycle management.

What is Apache Airflow?

Airflow is an open-source platform that facilitates the programmatic design, scheduling, and oversight of workflows, driven by community contributions. Its architecture is designed for flexibility and utilizes a message queue system, allowing for an expandable number of workers to be managed efficiently. Capable of infinite scalability, Airflow enables the creation of pipelines using Python, making it possible to generate workflows dynamically. This dynamic generation empowers developers to produce workflows on demand through their code. Users can easily define custom operators and enhance libraries to fit the specific abstraction levels they require, ensuring a tailored experience. The straightforward design of Airflow pipelines incorporates essential parametrization features through the advanced Jinja templating engine. The era of complex command-line instructions and intricate XML configurations is behind us! Instead, Airflow leverages standard Python functionalities for workflow construction, including date and time formatting for scheduling and loops that facilitate dynamic task generation. This approach guarantees maximum flexibility in workflow design. Additionally, Airflow’s adaptability makes it a prime candidate for a wide range of applications across different sectors, underscoring its versatility in meeting diverse business needs. Furthermore, the supportive community surrounding Airflow continually contributes to its evolution and improvement, making it an ever-evolving tool for modern workflow management.

Media

Media

Integrations Supported

Google Cloud Managed Service for Apache Airflow
Azure Kubernetes Fleet Manager
Fivetran
IBM DataStage
Jenkins
Oracle Database
SAP Datasphere
SAP Integrated Business Planning (IBP)

Integrations Supported

Google Cloud Managed Service for Apache Airflow
AT&T Alien Labs Open Threat Exchange
Datus
JAMS Scheduler
LocalStack
Meltano
Orchestra
Pantomath
Ray
SDF
Secoda
Zipher
intermix.io

API Availability

Has API

API Availability

Pricing Information

$2400 / month

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

BMC Software

Date Founded

1980

Company Location

United States

Company Website

www.bmc.com/it-solutions/control-m.html

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

airflow.apache.org

Categories and Features

Data Pipeline

Not specified

DataOps

Not specified

DevOps

Not specified

IT Automation

Not specified

Job Scheduler

Not specified

Managed File Transfer (MFT)

API Integration
Authentication / Auditing
Data Sharing
Database Management

Runbook Automation

Not specified

Secure File Transfer

Not specified

Workload Automation

Alerts / Notifications
Audit Trails
Business Process Management
Cross-Platform Scheduling
Dashboard
Data Analysis / Visualization
Event-Triggers
Load Balancing
Resource-Based Scheduling
Robotic Process Automation (RPA)
Workflow Foundation Support

Categories and Features

AI Orchestration

Not specified

Data Pipeline

Not specified

DataOps

Not specified

Job Scheduler

Not specified

Workflow Management

Not specified

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