Easily integrate real-time data to Azure Cosmos DB from a wide variety of data sources.
To run operational workloads on Azure Cosmos DB and support highly responsive and highly available applications worldwide, you need real-time data pipelines from legacy and other cloud systems. 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 Azure Cosmos DB in a consumable form with sub-second latency to easily run critical transactional and analytical workloads in Azure.
Benefits: Striim eases extending your data center to Azure by continuously moving real-time data to Azure Cosmos DB.
- 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 Cosmos DB by providing more timely and relevant data
- Migrate to Cosmos DB from MongoDB and others without impacting business operations
- Optimize data storage by ingesting only the data you need
Features: Striim is a secure, reliable and scalable service for non-intrusive, real-time data ingestion from databases (via low-impact CDC), data warehouses, log files, messaging systems, sensors, Hadoop, and NoSQL solutions with in-flight transformation and optimized delivery.
- Fast-to-deploy, template-based service for real-time data integration from databases (incl. Oracle, SQL Server, HPE NonStop, PostgreSQL, MySQL, MongoDB, and Amazon RDS), 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 Cosmos DB from existing databases by running them in parallel.
Unlike ETL solutions, Striim continuously ingests granular data sets for richer reporting and 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 typ