Move Data to Amazon Redshift In Real Time From a Wide Variety of Data Sources

The Striim platform, running in AWS as a PaaS solution, provides low-impact, real-time data ingestion from data warehouses (including Oracle Exadata, Teradata), databases (including Oracle, SQL Server, HPE NonStop, MySQL and PostgreSQL), log files, messaging systems, sensors, and Hadoop solutions, with in-flight transformations and optimized delivery.

For real-time data movement from enterprise databases, Striim uses low-impact change data capture (CDC) to avoid performance impact on source production systems.

By continuously streaming updated business data in a consumable format to Amazon Redshift, Striim eases cloud-based analytics and supports operational decision making.

Why Striim for Amazon Redshift

Designed for mission-critical environments, Striim enables secure, reliable, and scalable real-time data pipelines for unstructured, semi-structured, and structured data into Amazon Redshift. Redshift customers can store the data in the right format, and provide full context for any downstream operations, such as reporting and analytical applications.

With wizards and a drag-and-drop UI, Striim accelerates data pipeline development. Striim also offers out-of-the-box, exactly once processing capabilities.

Using SQL-based, in-flight transformations including denormalization, Striim reduces on-premises ETL workloads as well as data latency. Compared to an ELT architecture, using a single solution to orchestrate the end-to-end data flow with in-flight transformations eliminates network hops, and simplifies recovery after outages.

Simplifying a Modern Cloud Data Warehouse
  • Stream real-time data to Amazon Redshift from on-premises data sources to gain more operational value from your modern data warehouse solution
  • Process data-in-motion to load the data in a consumable format and accelerate time-to-insight
  • Avoid batch ETL-related inefficiencies using an end-to-end solution with non-intrusive CDC and in-flight data processing
  • Update traditional ETL processes with streaming data integration to fully benefit from next-gen cloud-based analytics