Define, launch, and monitor ETL and ELT pipeline activities
Integrate Azure Data Factory workflows into overall business processes
Apply advanced data flow scheduling functionality to the Azure Data Factory pipeline
The native Azure scheduler, Azure Logic Apps, offers basic scheduling functionality limited to Azure solutions. With Tidal’s adapter for Azure Data Factory (ADF), you can replace the native Azure scheduler and gain enhanced control over ADF tasks.
Our ADF Adapter integrates seamlessly with integration runtimes and integration services, ensuring smooth data integration and transformation processes. It enables the scheduling and management of linked services, allowing you to connect and orchestrate data movement across various systems and platforms.
As a data engineer or a DevOps professional, you’ll find our ADF Adapter invaluable in orchestrating and automating data workflows. Our adapter expands ADF’s capabilities by enabling seamless connectivity to various data sources and destinations, including Azure Blob Storage, Azure Data Lake, Azure SQL Database, Azure Synapse, and even on-premises resources such as SQL Server and SSIS. It allows you to automate data pipelines and ensure the timely delivery of business-critical data to the right place at the right time.
In this brief video, get an overview of our adapter for Azure Data Factory (ADF). See a brief demo of how the integration optimizes data management and integrates with Azure functions.
OUR CORE PLATFORM
A unified platform for centralized management and control of job scheduling across business, operations and IT processes. Tidal Automation Platform >
Tidal provides advanced functionality and integration options, allowing users to efficiently manage and manipulate data across various Azure resources.
You can easily work with data warehouses and data stores, ensuring seamless integration and optimal performance. Users can handle datasets effectively, including working with JSON-based datasets, providing data processing and transformation flexibility.
Tidal's ADF adapter also integrates with Azure resources like HDInsight, Hive, Power BI, and supports REST API integration, enabling users to interact with its functionality and automate various tasks programmatically.
Tidal's adapter for Azure Data Factory streamlines job scheduling by providing advanced features and functionality within the Azure portal, considering various factors such as data flow and data transformation requirements. It empowers you to schedule pipeline runs efficiently, considering start dates, start times, and time zones (such as UTC).
Our adapter provides comprehensive scheduling options, including schedule triggers, window triggers, the ability to add triggers, and trigger pipeline execution on demand. You can utilize templates to streamline the creation and management of complex data workflows while benefiting from built-in functions to transform and manipulate data.
Optimize your data integration and migration processes, define cross-application dependencies, and achieve efficient data management across your enterprise.
Yes, Tidal's adapter for Azure Data Factory empowers users to transform data seamlessly and integrate with machine learning workflows. The adapter enables efficient data processing and manipulation by leveraging powerful tools like Spark and Python.
Whether you need to perform advanced analytics, apply machine learning algorithms, or execute custom actions with PowerShell scripts, the adapter provides the necessary capabilities for comprehensive data transformation.
Our adapter empowers you to achieve efficient data management and orchestration with robust scheduling options, including support for time-based triggers and tumbling windows.
Tidal also integrates with Azure Databricks, enabling advanced analytics and data processing capabilities within Azure Data Factory pipelines.