Striim simplifies real-time data integration to Azure Storage solutions – including Data Lake Storage (Gen 1 and Gen 2) and Blob Storage – from a wide variety of sources. You can continuously deliver data from enterprise databases via log-based change data capture (CDC), cloud environments, log files, messaging systems, sensors, and Hadoop solutions.
The Striim solution enables you to quickly build streaming data pipelines with your desired data latency (real-time, micro-batch, or batch) and enrich the data with additional context. These pipelines can then support any application or advanced analytics / machine learning solutions – including Azure SQL Data Warehouse and Azure Databricks – that use Azure Storage services. With access to timely data in the right format, your data operations teams can significantly reduce the preparation effort for analytics, and your organization can achieve faster time-to-insight.
Striim offers a secure, reliable, and scalable service, running in the Azure Cloud, for real-time collection, preparation, and delivery of unstructured, semi-structured, and structured data into Azure Storage. It supports major databases with non-intrusive CDC capabilities including Oracle, SQL Server, HPE NonStop, MySQL, MongoDB, Amazon RDS for Oracle, Amazon RDS for MySQL.
While the data is streaming, Striim performs in-flight filtering, transformation, masking, aggregation, and enrichment before delivering to Azure Storage. With in-memory stream processing, it enables customers to store the data in the right format without inefficient batch ETL cycles, and accelerates access to processed data. Striim’s wizard-based, drag-and-drop design interface speeds deployment and time-to-value for Azure solutions.
Easily integrate with a variety of Azure services including Azure Databricks and HDInsight
Speed deployment and time-to-value for Azure solutions
Make data available with lower latency without burdening data sources