Striim moves real-time data from virtually any data source, including enterprise databases via log-based change data capture (CDC), other cloud environments, log files, messaging systems, sensors, and Hadoop data into AWS. AWS customers can rapidly build real-time data pipelines to Amazon Redshift, Amazon S3, Amazon RDS for Oracle, Amazon RDS for SQL Server, Amazon RDS for MySQL, Amazon Aurora, and Amazon Kinesis services to enable up-to-date data for critical workloads in the cloud.
Striim offers real-time collection, preparation, and delivery of unstructured, semi-structured, and structured data into multiple different Amazon environments.
For major databases, including Oracle, SQL Server, HPE NonStop, MySQL, Amazon RDS for Oracle, Amazon RDS for MySQL, it offers non-intrusive change data capture (CDC) capabilities. Without inefficient batch cycles, Striim performs in-line data transformation, including denormalization, and enrichments using SQL-based language before loading the data in real time.
The Striim platform can also be deployed in the AWS environment with a BYOL model to implement various use cases beyond integration to AWS services. These use cases include real-time data integration for enterprise databases, Apache Kafka, Apache Hadoop, Apache Cassandra, and other cloud environments.
Striim’s wizard-based, drag-and-drop design interface speeds deployment and time to market for new solutions.
Run operational workloads in RDS for Oracle, RDS for MySQL, RDS for SQL Server, Aurora MySQL by delivering data from on-prem and other cloud solutions in real time
Easily offload high-value workloads to AWS by continuously loading real-time data from operational systems
Pre-process your enterprise data through filter, transform, enrich and join operators in real time as it is being delivered into AWS
Enable bi-directional data synchronization between your cloud and on-prem environments