List of the Top 5 Data Pipeline Software for Control-M in 2026

Reviews and comparisons of the top Data Pipeline software with a Control-M integration


Below is a list of Data Pipeline software that integrates with Control-M. Use the filters above to refine your search for Data Pipeline software that is compatible with Control-M. The list below displays Data Pipeline software products that have a native integration with Control-M.
  • 1
    Matillion Reviews & Ratings

    Matillion

    Matillion

    Revolutionize data transformation: fast, scalable, cloud-native efficiency.
    Introducing a groundbreaking cloud-native ETL solution designed to efficiently load and transform data for your cloud data warehouse. We have redefined the traditional ETL model by creating a tool that operates directly in the cloud environment. Our cutting-edge platform harnesses the nearly limitless storage capabilities of the cloud, allowing your projects to scale to unprecedented levels. Operating within the cloud environment simplifies the complexities involved in transferring large volumes of data significantly. Experience the remarkable capability of processing a billion rows of data in just fifteen minutes, and enjoy a swift transition from launch to operational functionality in as little as five minutes. In an era where competition is fierce, organizations must effectively utilize their data to reveal critical insights. Matillion streamlines your data transformation process by efficiently extracting, migrating, and transforming your data in the cloud, enabling you to gain new insights and improve your strategic decision-making. This positions businesses to remain competitive and agile in an ever-changing market landscape, ensuring they are always ready to adapt to new challenges and opportunities.
  • 2
    Fivetran Reviews & Ratings

    Fivetran

    Fivetran

    Effortless data replication for insightful, rapid decision-making.
    Fivetran is a market-leading data integration platform that empowers organizations to centralize and automate their data pipelines, making data accessible and actionable for analytics, AI, and business intelligence. It supports over 700 fully managed connectors, enabling effortless data extraction from a wide array of sources including SaaS applications, relational and NoSQL databases, ERPs, and cloud storage. Fivetran’s platform is designed to scale with businesses, offering high throughput and reliability that adapts to growing data volumes and changing infrastructure needs. Trusted by global brands such as Dropbox, JetBlue, Pfizer, and National Australia Bank, it dramatically reduces data ingestion and processing times, allowing faster decision-making and innovation. The solution is built with enterprise-grade security and compliance certifications including SOC 1 & 2, GDPR, HIPAA BAA, ISO 27001, PCI DSS Level 1, and HITRUST, ensuring sensitive data protection. Developers benefit from programmatic pipeline creation using a robust REST API, enabling full extensibility and customization. Fivetran also offers data governance capabilities such as role-based access control, metadata sharing, and native integrations with governance catalogs. The platform seamlessly integrates with transformation tools like dbt Labs, Quickstart models, and Coalesce to prepare analytics-ready data. Its cloud-native architecture ensures reliable, low-latency syncs, and comprehensive support resources help users onboard quickly. By automating data movement, Fivetran enables businesses to focus on deriving insights and driving innovation rather than managing infrastructure.
  • 3
    Google Cloud Managed Service for Apache Airflow Reviews & Ratings

    Google Cloud Managed Service for Apache Airflow

    Google

    Simplify and scale your data workflows effortlessly today!
    Managed Service for Apache Airflow is a comprehensive workflow orchestration platform from Google Cloud that enables organizations to build, schedule, and monitor complex data pipelines with ease. Based on the open-source Apache Airflow project, it uses Python-defined DAGs to create flexible and scalable workflows. The fully managed nature of the service removes the burden of infrastructure management, allowing teams to focus on data engineering and automation tasks. It integrates seamlessly with Google Cloud services such as BigQuery, Dataflow, Managed Service for Apache Spark, Cloud Storage, and Pub/Sub, enabling end-to-end pipeline orchestration. The platform supports hybrid and multi-cloud environments, making it ideal for organizations with diverse data ecosystems. It includes advanced features like DAG versioning, scheduler-managed backfills, and improved user interfaces for better workflow management. Built-in monitoring, logging, and visualization tools help ensure reliability and simplify troubleshooting. The service also supports CI/CD pipelines, enabling automated deployment and management of workflows. Its open-source foundation ensures portability and flexibility while avoiding vendor lock-in. Security features such as IAM, VPC Service Controls, and encryption provide strong data protection. The platform is suitable for a wide range of use cases, including ETL pipelines, machine learning workflows, and business intelligence automation. It also enables event-driven and near real-time pipeline execution. Overall, Managed Service for Apache Airflow provides a robust, scalable, and user-friendly solution for orchestrating modern data workflows.
  • 4
    Databricks Reviews & Ratings

    Databricks

    Databricks

    Empower your organization with seamless data-driven insights today!
    The Databricks Data Intelligence Platform empowers every individual within your organization to effectively utilize data and artificial intelligence. Built on a lakehouse architecture, it creates a unified and transparent foundation for comprehensive data management and governance, further enhanced by a Data Intelligence Engine that identifies the unique attributes of your data. Organizations that thrive across various industries will be those that effectively harness the potential of data and AI. Spanning a wide range of functions from ETL processes to data warehousing and generative AI, Databricks simplifies and accelerates the achievement of your data and AI aspirations. By integrating generative AI with the synergistic benefits of a lakehouse, Databricks energizes a Data Intelligence Engine that understands the specific semantics of your data. This capability allows the platform to automatically optimize performance and manage infrastructure in a way that is customized to the requirements of your organization. Moreover, the Data Intelligence Engine is designed to recognize the unique terminology of your business, making the search and exploration of new data as easy as asking a question to a peer, thereby enhancing collaboration and efficiency. This progressive approach not only reshapes how organizations engage with their data but also cultivates a culture of informed decision-making and deeper insights, ultimately leading to sustained competitive advantages.
  • 5
    Apache Airflow Reviews & Ratings

    Apache Airflow

    The Apache Software Foundation

    Effortlessly create, manage, and scale your workflows!
    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.
  • Previous
  • You're on page 1
  • Next