Our needs for real-time data are growing at an unprecedented rate; it is only a matter of time before you will be faced with building a real-time streaming pipeline. Often a major key decision you would need to quickly make is which stream-processing framework should you use. What if instead you could use a unified API that allows you to express complex data processing workflows, including advanced windowing and event timing and aggregate computations? Apache Beam aims to provide this unified model along with a set of language-specific SDKs for defining and executing complex data processing, data ingestion and integration workflows. This simplifies and will truly change how we implement and think about large-scale batch and streaming data processing in the future. Today these pipelines can be run on Apache Flink, Apache Spark, and Google Cloud Dataflow.

This is only a start, come to this session to learn where the future of streaming API’s is headed and get ready to leverage Apache Beam for your next streaming project.