Enterprise streaming solution for hybrid data management

Providing a single, comprehensive, and scalable enterprise-grade streaming data management solution to support all use cases and deployment models.

Tuesday, 7th May 2019 Posted 5 years ago in by Phil Alsop

Informatica is offering the first enterprise data streaming and ingestion solution for hybrid deployments, enabling enterprises to make insightful, data-driven business decisions in real-time. The single solution allows users to adapt to emerging and rapidly changing streaming technologies to process massive amounts of data, manage complex deployments, and make decisions at the speed of business.

The explosion of data is increasing yearly, with 20.6 zettabytes in global data center traffic by 2021 and 500 million business data users and growing.

Effective streaming data management now requires:

Ingesting data at scale from any source, including real-time streams, files, databases and database change data capture, whether on-premises or in the cloud
Processing data at any latency, both real-time streaming and batch
Leveraging industry leading streaming and big data processing technologies such as Apache Spark, Spark Structured Streaming, Kafka, and more
Driving order of magnitude automation and recommendations with AI and machine learning
Supporting a hybrid, multi-cloud environment

The Informatica^® Enterprise Streaming and Ingestion solution supports streaming data ingestion from a broad variety of sources, such as internet of things, machine and sensor data. The solution also includes change data capture for databases as well as connectivity to files, databases, apps and more, both on-premises and in the cloud. It is the industry’s first solution to support Structured Streaming from Apache Spark for multi-latency data processing while leveraging the power of the Informatica CLAIRE™ engine for intelligent structure discovery and dynamically evolving schemas.

In Gartner’s recent report, “Adopt Stream Data Integration to Meet Your Real-Time Data Integration and Analytics Requirements,” published on March 15, 2019 by Ehtisham Zaidi, W. Roy Schulte, and Eric Thoo, it is noted, “By 2023, over 70% of organizations will use more than one data delivery style to support their data integration use cases, resulting in preference for tools than can support the combination of multiple data delivery styles (such as ETL and stream data integration.”