Hybrid data integration service that simplifies ETL at scale
Accelerate data integration
Integrate data silos with Azure Data Factory, a service built for all data integration needs and skill levels. Easily construct ETL and ELT processes code-free within the intuitive visual environment, or write your own code. Visually integrate data sources using more than 90+ natively built and maintenance-free connectors at no added cost. Focus on your data—the serverless integration service does the rest.
No code or maintenance required to build hybrid ETL and ELT pipelines within the Data Factory visual environment
Cost-efficient and fully managed serverless cloud data integration tool that scales on demand
Azure security measures to connect to on-premises, cloud-based, and software-as-a-service apps with peace of mind
SSIS integration runtime to easily rehost on-premises SSIS packages in the cloud using familiar SSIS tools
Improve productivity with shorter time to market
Develop simple and comprehensive ETL and ELT processes without coding or maintenance. Ingest, move, prepare, transform, and process your data in a few clicks, and complete your data modeling within the accessible visual environment. The managed Apache Spark™ service takes care of code generation and maintenance.
Reduce overhead costs
When migrating your SQL Server DB to the cloud, preserve your ETL processes and reduce operational complexity with a fully managed experience in Azure Data Factory. Rehost on-premises SSIS packages in the cloud with minimal effort using Azure SSIS integration runtime. ETL in Azure Data Factory provides you with the familiar SSIS tools you know.
Transfer data using prebuilt connectors
Access the ever-expanding portfolio of more than 90+ prebuilt connectors—including Azure data services, on-premises data sources, Amazon S3 and Redshift, and Google BigQuery—at no additional cost. Data Factory provides efficient and resilient data transfer by using the full capacity of underlying network bandwidth, delivering up to 4 GB/s throughput.
Integrate data cost-effectively
Integrate your data using a serverless tool with no infrastructure to manage. Pay only for what you use, and scale out with elastic capabilities as your data grows. Transform data with speed and scalability using the Apache Spark engine in Azure Databricks. Integrate expanded datasets from external organizations. Use Azure Data Share to accept new datasets into your Azure analytics environment, then use Data Factory to integrate them into your pipelines to prepare, transform, and enrich your data to generate insights.
Work the way you want
Data Factory provides a single hybrid data integration service for all skill levels. Use the visual interface or write your own code in Python, .NET, or ARM to build pipelines. Put your choice of processing services into managed data pipelines, or insert custom code as a processing step in any pipeline.
Get continuous integration and delivery (CI/CD)
Continuously monitor and manage pipeline performance alongside applications from a single console with Azure Monitor. Integrate your DevOps processes using the built-in support for pipeline monitoring. If you prefer a less programmatic approach, use the built-in visual monitoring tools and alerts.
Trusted, global cloud presence
- Access Data Factory in more than 25 countries/regions. The data-movement service is available globally to ensure data compliance, efficiency, and reduced network egress costs.
- Data Factory is certified by HIPAA, HITECH, ISO/IEC 27001, ISO/IEC 27018, and CSA STAR.
- Protect your data while it’s in use with Azure confidential computing. Data Factory management resources are built on Azure security infrastructure and use all the Azure security measures.
Pay only for what you need, with no upfront cost
Explore a range of cloud data integration capabilities to fit your scale, infrastructure, compatibility, performance, and budget needs. Options include managed SSIS for seamless migration of SQL Server projects to the cloud, and large-scale, serverless data pipelines for integrating data of all shapes and sizes.Data Factory Pricing
Data Factory Resources
Mapping Data Flows
Develop graphical data transformation logic at scale without writing code using Mapping Data Flows.
Use the expanding library of templates for common tasks such as building pipelines, copying from a database, executing SSIS packages in Azure, and ETL.
Automate pipeline runs by creating and scheduling triggers. Data Factory supports three types of triggers: schedule, tumbling window, or event-based.
Wrangling Data Flows
Explore your data at scale without writing code. Use Wrangling Data Flows, now in public preview, for code-free data preparation at scale.
Visually construct workflows to orchestrate data integration and data transformation processes at scale.
Trusted by companies of all sizes
Global manufacturer uses big data to help employees work smarter
Reckitt Benckiser (RB), which makes consumer health, hygiene, and home products, replaced its business intelligence solution with Microsoft Power BI and Azure.
Cardiovascular information system provider prescribes an Rx for speed
LUMEDX uses Data Factory to produce insights in a fraction of the time it previously took. The California-based company provides information systems that consolidate the images and data cardiologists use to plan patient care.
Businesses predict weather impact using cloud-based machine learning
Nearly 2 billion people worldwide rely on AccuWeather forecasts. AccuWeather uses Azure Machine Learning to create custom weather-impact predictions for business customers and transform its own business faster.
New to Azure? Here’s how to get started with Data Factory
Documentation and resources
Browse Data Factory videos for overviews, how-tos, and demos of key features and capabilities.
Frequently asked questions about Data Factory
We guarantee we will successfully process requests to perform operations against Data Factory resources at least 99.9 percent of the time. We also guarantee that all activity runs will initiate within four minutes of their scheduled execution times at least 99.9 percent of the time. Read the full Data Factory service-level agreement (SLA).
Integration runtime (IR) is the compute infrastructure Data Factory uses to provide data integration capabilities across network environments. IR moves data between the source and destination data stores while providing support for built-in connectors, format conversion, column mapping, and scalable data transfer. IR provides the capability to natively execute SSIS packages for dispatch activities and natively executes SSIS packages in a managed Azure compute environment. It supports dispatching and monitoring of transformation activities running on several compute services. For more information, see integration runtime in Data Factory.