Informatica announces streaming solution for hybrid data management
Informatica announced it 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 centre 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 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
Informatica SVP Ronen Schwartz says, “Our customers rely on streaming data management for everything from fraud alert detection, to dynamic pricing and offers, all the way to monitoring patient data in real time.
“To do this, they require a single, comprehensive solution that ingests and processes data from any source, at any latency, and in any environment.”
“The Informatica Enterprise Data Streaming and Ingestion solution provide unparalleled capabilities, now available from one vendor, to support all real-time use cases in a single solution.”
The solution supports streaming data ingestion from a broad variety of sources, such as the internet of things, machine and sensor data.
The solution also includes changing data capture for databases as well as connectivity to files, databases, apps and more, both on-premises and in the cloud.
It is supposedly 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.