US: Cloud and big data solutions provider Talend has a new set of connectors for Talend Data Fabric to provide customers with accelerated data migration to Microsoft Azure Cloud. The new Talend Data Fabric connectors are intended to enable customers to build intelligent, scalable data pipelines for real-time big data analytics in cloud.
Talend Data Fabric previously connected customers to Microsoft Azure HDInsight and Blob Storage. The new connectors are also compatible with Microsoft Azure SQL Data Warehouse, SQL Database, Azure CosmosDB, Data Lake Store, Queue Storage and Table Storage.
With the new Talend Data Fabric connectors, Azure developers can simplify the creation of cloud data pipelines and quickly migrate on-premises data to the Azure cloud. Big data analytics are enabled using Spark-powered data matching and machine learning. The Talend Data Fabric connectors also assist in security management and data configuration for big data clusters, improving DevOps productivity.
Clients are also now able to integrate streaming data and historical data, so not only does Talend integrate big data uploads for real-time analysis, it also allows for contextual insights based on analysis of past data.
Ashley Stirrup, CMO of Talend, stressed the importance of combining on-prem, legacy data systems with cloud-powered big data analysis.
“Teaming with Microsoft allows us to deliver a complete solution for scaling big data workloads in the cloud. While other data integration solutions only connect with a few data sources, our Summer ’17 release of Talend Data Fabric includes in-depth, native functionality to help customers quickly migrate a broad range of on-premise data sources to the Azure cloud and optimize cloud data pipelines, speeding time to insight.”
Last month, Talend partnered with Disy to release a geospatial connector for the Talend Data Fabric. The new geospatial connector connects different geographical information databases, including Oracle Locator/Spatial, automating tasks and geospatial workflows to assist in the analysis of customer location data and usage.