Cloud-Based Analytics Upgraded in Striim’s Platform

Enterprise-grade streaming data platform provider Striim has announced the availability of version 3.8.4 of the Striim platform. The new release’s features increase streaming data integration and the operational value of cloud analytics. They also help organizations transition to and use cloud-based analytics via real-time data pipelines that feed different layers of their cloud environment. The platform — available as a cloud service — offers scalability and real-time data movement.

“To deliver next generation digital transformation, businesses are quickly moving to cloud-based analytics,” says Alok Pareek, founder and EVP of Products at Striim. “With Striim 3.8.4, users can set up real-time and pre-processed data flows from on-premises and cloud environments into different layers of their cloud solution to accelerate their onboarding and increase the operational value gained from their analytical solutions in the cloud.”

See also: Streaming analytics resource center by Striim

The 3.8.4 upgrade brings real-time data to:

• Analytics services and data warehousing solutions — like Azure SQL Data Warehouse and Google BigQuery — that directly support end users with timely intelligence
• Data management and analytics frameworks — like Azure HDInsight — that support interactive analysis or create machine learning models
• Storage solutions — like Amazon S3 or Azure Data Lake Storage — from on-premises and other cloud-based data sources in real time
• Staging areas — like HDFS, S3, ADLS — used by other cloud services and components

The company has also:

• Improved its real-time data integration into Amazon S3
• Automated streaming data integration to Hive solutions
• Added Schema Registry support for Apache Kafka
• Introduced Open Processor and Continuous Data Processing Validation
• Added support for Microsoft Azure Database for PostgreSQL and Microsoft Azure Database for MySQL