SnapLogic Introduces Intelligent Connectors for Microsoft Azure Data Lake Store
SnapLogic announced the availability of new pre-built intelligent connectors – called Snaps – for Microsoft Azure Data Lake Store. The new Snaps provide fast, self-service data ingestion and transformation from virtually any source – whether on-premises, in the cloud or in hybrid environments – to Microsoft’s highly-scalable, cloud-based repository for big data analytics workloads. This latest integration between SnapLogic and Microsoft Azure helps enterprise customers gain new insights and unlock business value from their cloud-based big data initiatives.
The Microsoft Azure Data Lake Store is hyper-scale repository for big data analytics. With SnapLogic, users can ingest data from any source and in any format to Microsoft Azure Data Lake Store for further processing on an HDInsight cluster. Timely, relevant data can then be delivered for analysis to a variety of business intelligence tools or off-cluster data stores.
“As data gravity continues to move to the cloud, enterprises require a modern, agile platform to manage the massive volumes and varieties of data increasingly being stored and processed in data lakes,” said Craig Stewart, vice president of product management at SnapLogic. “Together with Microsoft, we are making it easier and faster for our customers to turn big data in the cloud into intelligent, actionable insights that in turn deliver meaningful value to the business.”
This announcement continues SnapLogic’s ongoing collaboration with Microsoft and follows recent developments including:
- SnapLogic’s support of Microsoft HDInsight, Microsoft’s cloud-based Hadoop distribution that supports managed processing of structured, semi-structured and unstructured data
- The availability of SnapLogic’s hybrid execution framework for Microsoft Azure – the Azureplex – on the Microsoft Azure marketplace
- SnapLogic also offers Snaps for Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL Database and Microsoft Azure Blob Storage