Data Engineering Streaming

Unleash the power of real-time analytics with trusted, low-code IoT and stream processing.



Key Features

Informatica Data Engineering Streaming empowers analytics with no limits on real-time streaming data processing.

Real-time data ingestion and integration

Ingest events quickly and easily from real-time queues to derive maximum value. Seamlessly integrate and transform streaming data in real time.

Spark structured streaming

Manage multi-latency data in a single platform and source event-time based processing. Turn out-of-order source data into in-order data.

Enhanced connectivity

Ingest and process real-time streaming data into AWS S3, Amazon Kinesis, Microsoft Azure Data Lake Storage (ADLS), Azure Event Hub, and Kafka with enhanced connectivity

Advanced streaming data transformation

Apply data quality transformations on streaming data with a common UI for batch and streaming integration.

Cloud-ready stream support

Ingest, process, and manage real-time streaming data that supports Amazon Kinesis and Kafka as source, Amazon Kinesis Firehose and Microsoft Azure Event Hub as target, and Amazon EMR in streaming mode.

Alignment with Informatica Data Engineering Integration

Capture changed data and real-time data and provide data management to filter, transform, aggregate, enrich, and process it before delivering it for analytics via AI and ML.

Intelligent stream data parsing

Automatically parse Avro messages in Kafka using Confluent Schema and parse complex streaming data with intelligent structure discovery powered by the Informatica CLAIRE™ engine. Easily handle schema drift and evolving sche

Quality of service

Get reliable data delivery with automated failover and easy capacity scaling.

Customer Success Stories


Jewelry TV achieves real-time view into marketing analytics with Informatica.


OVO drives real-time customer experience with AI-powered streaming analytics.


Avis Budget Group disrupts the vehicle rental industry with real-time analytics.