Striim for Real-Time Integration to Azure Storage

Striim, Inc.
Easily integrate real-time data to Azure Storage from a wide range of data sources.

Striim for Real-Time Integration to Azure Storage

Striim, Inc.

Easily integrate real-time data to Azure Storage from a wide range of data sources.

Offloading data center management to the Azure Cloud requires continuously collecting all your critical data from legacy systems. The Striim® platform is an enterprise-grade streaming data integration solution that continuously ingests, processes, and delivers high volumes of streaming data from diverse sources, on-premises or in the cloud. Cloud architects, data architects, and data engineers can use Striim to quickly build streaming data pipelines to Azure Blob Storage and Azure File Storage choosing their desired data latency (real-time, micro-batch, or batch) and enrich with context to supply the required data to Azure solutions, and optimize their storage.

Benefits: Striim eases extending your data center to Azure by continuously moving real-time data to Azure Storage.

  • Raise IT productivity and accelerate time-to-value, while reducing cost of ownership, by integrating data from a wide range of sources using a wizard-based UI
  • Increase the operational value gained from solutions that use Azure Storage by providing more timely and relevant data
  • Ingest and store only the data you need, in the format you need

Features: Striim is a secure, reliable and scalable service for non-intrusive, real-time data ingestion from databases (via low-impact CDC), data warehouses, log files, messaging systems, sensors, Hadoop, and NoSQL solutions with in-flight transformations and optimized delivery.

  • Fast-to-deploy, template-based service for real-time data integration from databases (incl. Oracle, Exadata, SQL Server, HPE NonStop, PostgreSQL, MySQL, MongoDB, Teradata, and Amazon RDS), Amazon S3, log files, Hadoop, Salesforce, IoT (MQTT, OPC UA) and messaging systems.
  • In-line filtering and transformations using a SQL-based language reduce end-to-end latency, optimize storage, and support operational use cases.

Unlike ETL solutions, Striim continuously ingests granular data sets for richer reporting and analytics without impacting sources, and processes the streaming data in-memory for sub-second latency. Striim differs from logical replication with its support for a wide range of data types, sources, and targets, and out-of-the-box stream processing capabilities.