Easily integrate real-time data to Azure SQL Data Warehouse from a wide variety of data sources
Building real-time data pipelines from existing systems to a new cloud-based data warehouse can be a difficult pre-requisite to get the most value from Azure. The Striim® platform is an enterprise-grade streaming data integration solution that continuously ingests, processes, and delivers high volumes of streaming data from diverse sources, on-premises or in the cloud. Cloud architects, data architects, and data engineers can use Striim to move data into SQL Data Warehouse in a consumable form, quickly and with sub-second latency to implement a modern, real-time data warehousing solution.
Benefits: Striim eases cloud-based analytics and supports operational decision making by continuously moving data to Azure SQL DW.
- Increase IT productivity, while reducing cost of ownership, by integrating and enriching data from wide variety of sources
- Increase the value of applications that use Azure SQL DW by providing more timely and relevant data
- Migrate to Azure SQL DW without impacting business operations
- Maximize the lifetime of the Azure environment by storing only the relevant data you need
Features: Striim is a secure, reliable and scalable service for non-intrusive, real-time data ingestion from data warehouses, databases, log files, messaging systems, sensors, and Hadoop solutions with in-flight transformations and optimized delivery.
- Fast-to-deploy, template-based service for real-time data integration from data warehouses (incl. Oracle Exadata, Teradata, and Amazon Redshift), databases (incl. Oracle, SQL Server, HPE NonStop, MongoDB, Amazon RDS and MySQL), log files, Hadoop, Salesforce, IoT (MQTT, OPC UA) and messaging systems.
- In-line transformations reduce end-to-end latency, and enable real time analytics and operational reporting workloads.
- Zero database downtime migration to Azure SQL DW from existing data warehouses by running them in parallel.
Unlike ETL solutions, Striim continuously ingests granular data sets for richer analytics without impacting sources, and processes the streaming data in-memory for sub-second latency. Striim differs from logical replication tools with its support for a wide range of data types, data sources, and targets, and out-of-the-box stream processing capabilities.