Striim enables continuous real-time data movement and processing for hybrid cloud, connecting on-prem data sources and cloud environments, as well as bridging a wide variety of cloud services across Microsoft Azure, AWS, and Google Cloud platforms. With in-memory stream processing for hybrid cloud, Striim allows you to store only the data you need, in the format you need. And Striim’s built-in delivery validation and data pipeline monitoring ensures pipeline health and replication verification in real time.
Why Striim for Data Movement and Processing for Hybrid Cloud
Striim automates and simplifies real-time streaming data pipelines for cloud environments. With its non-intrusive change data capture feature, Striim extracts real-time data without slowing down source transactional databases. Striim enables cloud migration with zero database downtime and minimized risk, and feeds real-time data to targets with full context – ready for rich analytics on the cloud – by performing filtering, transformation, aggregation, and enrichment on data in-motion.
Striim can run both on-premises, or in Azure, AWS and Google Cloud environments as a Service (PaaS) offering, allowing a flexible data management architecture.
- Offload operational workloads to cloud by easily moving data across different cloud service providers: Azure, AWS, and Google Cloud
- Filter, aggregate, transform, and enrich your data in-motion before delivering to the cloud in order to optimize cloud storage
- Migrate your data to the cloud without interrupting business operations
- Minimize risk of cloud migrations with real-time, built-in data delivery validation and data pipeline monitoring
Use Case: A European Express Parcel Company
This leading courier company in Europe enabled real-time data movement and processing for hybrid cloud solutions with the help of Striim. The company is moving its data warehousing and analytics solutions to the cloud, and uses Striim to move real-time data from transactional systems running on Oracle databases to Google BigQuery to enable cloud-based analytics. Google BigQuery serves as the operational data store supporting real-time reporting and ad-hoc queries. The company plans to use real-time transactional data for fleet optimization and real-time shipment status notifications to customers.
- Moved their operational data store (ODS) to the cloud by ensuring up-to-date transactional data is available in the cloud
- Eliminated the performance impact of running ad-hoc queries on the production OLTP systems
- Supports analytics users with timely data in a flexible and future-ready, cloud-based ODS and data warehouse solution
Use Case: Leading Canada-Based Global Bank
The leading Canadian retail bank has adopted a cloud-first strategy and wanted to move its financial reporting application to Azure. Striim, running on Azure, continuously captures existing data and newly arriving change data from Oracle database and HPE NonStop systems (without impacting their performance), processes the data while in-flight, and delivers to Azure Event Hubs in real time. Azure Event Hubs supports their operational reporting and other new applications in the cloud. Bank employees can now have 24/7 access to current financial information and make critical risk management and other operational decisions based on real-time data, versus the old method of using day-old data.
- Moves transactions from HPE NonStop to Azure Event Hubs in real time to run financial reporting in Azure
- Employees now make critical risk management and other operational decisions based on real-time data, versus the old method of using day-old data
- Easily executes on their cloud-first strategy by feeding real-time data to Azure to support new applications
To learn more about data movement and processing for hybrid cloud, please visit our Hybrid Cloud Integration solutions page, schedule a brief demo with a Striim technologist, or download a free trial of the Striim platform and try it for yourself!
