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Striim case study

Striim’s platform helps Azure HDInsight users enhance analytics workloads

A need for movement

Modern data analytics requires the continuous movement of high volumes of data into and out of Microsoft Azure HDInsight.

Striim and Azure HDInsight

The Striim platform moves data from on-premises and cloud-based data stores to Azure HDInsight in real time.

Enabling better decisions

With Striim, organizations can drive greater value from analytics apps on Azure HDInsight and gain real-time insights to guide decision making.

Striim, helping companies make data more useful from the start

Striim, founded in 2012, is headquartered in Palo Alto, California, and has been a Microsoft global partner since 2017. Striim helps businesses make timely and smart decisions using a modern streaming data architecture.

Through Azure HDInsight, companies can perform big data analytics with higher developer productivity and lower cost of management. When Azure customers sign up to use Azure HDInsight to run analytics workloads via Hadoop, Kafka, or Spark, they need to set up data flows to their environment. Striim’s end-to-end platform offers Azure users a secure, reliable, and scalable service for real-time movement of data from data warehouses, databases (via non-intrusive, minimal-impact change data capture), log files, messaging systems, Internet of Things sensors, and Hadoop solutions.

While moving the data, Striim filters, aggregates, transforms, masks, and enriches the streaming data to deliver it in a consumable format. Striim supports moving real-time data to Azure SQL Data Warehouse, Azure SQL Database, Azure Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure HDInsight, enabling users to make operational decisions based on time-sensitive data.

Real-time data ingestion and in-memory stream processing

Striim simplifies working with an agile and modern data architecture by replacing the traditional batch processing with non-intrusive streaming data integration. Striim supports high volumes of data with enterprise-grade redundancy, failover, recovery, check-pointing, security, and access control. Striim’s built-in delivery validation and data pipeline monitoring lowers risk and ensures pipeline health and replication verification.

In-memory stream processing allows only the data of interest to be moved, transforming it as needed in-flight, without additional latency. Azure HDInsight customers can store the data in the right format, helping them accelerate the insight gained from their analytics applications while better managing their limited data storage capacity.

Using Striim, organizations get greater value from cloud-based analytics. Real-time data ingestion for analytical processing enables businesses to make critical operational decisions. Running directly in an Azure HDInsight cluster, Striim can be deployed as part of Azure HDInsight services, making it convenient and simple to set up.

“Striim enables the continuous real-time movement of data both into Azure HDInsight and out from HDInsight, allowing companies to perform big data analytics with higher developer productivity and lower cost of management.”

—Alok Pareek, Founder and Executive Vice President of Products, Striim

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