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Templatize Microsoft and Azure Data Integration

Visualize, build, and manage the full lifecycle of data in any Microsoft and Azure data platform.

All the Data, None of the Friction

When too many tools, too much complexity, and too much hand coding slows your data integration down, you need a better way to provision data for Microsoft Azure Data Warehouse migration, Azure Data Lake ingestion, and taking advantage of SQL Server 2019 Big Data Clusters. 

StreamSets natively supports all the Microsoft and Azure data platforms, so you can use one platform for the entire Microsoft stack and beyond. A visual interface makes it easy to build and operate smart data pipelines that detect and respond to change and pre-built sources and destinations help you quickly connect to systems in the Microsoft ecosystem. 

DataOps agility for Microsoft SQL and Azure
Build smart data pipelines without hand coding
Easily detect and handle data drift
Detect, encrypt and mask sensitive data in motion

Native Integrations to Azure and SQL Server

Power your Microsoft and Azure data projects with rapid data integration. 

DataOps agility for Microsoft SQL Server
DataOps agility for Microsoft and HDInsight
DataOps agility for Microsoft Azure
DataOps agility for Azure Data Lake Store
DataOps agility for Azure and Databricks
Screenshot of customer 360 data lake on Microsoft Azure

Native Execution on

Easily move between on-premises and multiple cloud environments with native execution on these platforms:

  • Azure virtual machines (VMs) 
  • Azure Kubernetes
  • Azure HDInsight 
  • SQL Server 2019 Big Data Clusters 
  • Azure Databricks
Get it from Microsoft Azure Marketplace

Accelerate your Microsoft and Azure Projects

Modern data warehouse on Azure

Modern Data Warehouse on Azure

StreamSets makes it easy to migrate entire data sets from and into Azure Data Lake Storage (ADLS) Gen 1, Gen2, and Azure SQL databases. Auto-create partitions in ADLS and tables in Azure SQL.

Learn How

real-time analytics on azure

Migrate to a Cloud Data Lake

Migrating from an on-premises data lake to a cloud data lake does not have to take months or even weeks. With intent-driven data pipelines, you can migrate data from Hadoop FS to Azure Data Lake in hours.

Learn How

AI and machine learning on Azure

AI and Machine Learning

SQL Server 2019 Big Data Clusters provides an elastic data platform built exclusively using containerized applications, incorporating Apache Spark and HDFS plus SQL Server. Leverage the power of new engines like Apache Spark and scale out storage with the confidence and structure of Microsoft SQL.

Learn How

Power of Microsoft Hybrid without the Complexity

Detect and Respond to Data Drift

Other tools let you do data integration into SQL Server and Azure. But those data pipelines break when the unexpected happens, and they are hard to move to new data processing and cloud platforms. Only StreamSets Data Platform features smart data pipelines with built-in data drift detection and handling, and a hybrid cloud architecture, so that your operations run smoothly despite constant change.

Watch: Avoid Data Drift in Your Cloud Data Warehouse
Detect and respond to data drift with dataops agility on Microsoft Azure

Design-Deploy-Operate Continuously

In a static data world, up-front developer productivity matters more than operations. In a continuous data world, operations is everything. Close the loop between operations and development with automation and collaboration across the design-deploy-operate lifecycle. StreamSets Control Hub monitors data in flight to detect changes and predicts downstream issues to ensure continuous data delivery without errors or data loss. 

Watch: DataOps in Practice – Designing for Change
design, deploy, operate continuously with dataops agility on Microsoft Azure

Go Fast and Be Confident

When your business moves fast on a traditional architecture, things can break. But when you take your time, you fall behind. A purposeful data integration framework gives you end-to-end transparency across your data infrastructure, so you can detect emergent patterns and designs. A live data map, enforceable data performance SLAs and data protection help you focus on making data reliable as your users experiment and innovate. 

Watch: Next Gen Analytics at a Major Bank Using Azure Data Lake
DataOps transparency on Microsoft Azure

Lifting the Lid on the Hidden Data Integration Problem

Under-resourced technical teams struggle to keep up with business requests for data without ceding control, while business teams must have their data on demand to stay competitive. See solutions that reduce frustrations.

Creating Order from Chaos: Governance in the Data Wild West

Whitepapers & Ebooks

Data Engineer’s Handbook: 4 Cloud Design Patterns

4 Cloud Design Patterns for Data Ingestion and Transformation

Ready to Get Started?

We’re here to help you start building pipelines or see the platform in action.

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