The Apache Foundation this morning announced the promotion of Apache Beam to the top level. That’s good news for the many contributors and users of this unified programming model, which allows them to write batch and streaming jobs at the same time, and to run the resulting artifact on various execution engines.
Within the Hadoop world, there has been much movement around streaming and the faster performance of in-memory systems like Apache Spark on the batch front. One area that has continued to be troublesome for developers, however, has been the need to mix streaming data and historic data into the same processing systems.
Solutions such as Apache Flink and Apache Kafka have taken up the charge on the streaming side of the fence, but the batch jobs have been left out of this equation, for the most part. Beam solves this problem by providing developers with a unified programming model with which to build their data pipelines.
As it is an Apache project, Beam works with Apache Apex, Flink, Spark, and Google’s Cloud Dataflow.
Laurent Bride, CTO of Talend, said, “The graduation of Apache Beam as a top-level project is a great achievement and, in the fast-paced Big Data world we live in, recognition of the importance of a unified, portable, and extensible abstraction framework to build complex batch and streaming data-processing pipelines. Customers don’t like to be locked in, so they will appreciate the runtime flexibility Apache Beam provides. With four mature runners already available (and I’m sure more to come), Beam represents the future and will be a key element of Talend’s strategic technology stack moving forward.”
Ted Dunning, vice president of Apache Incubator and chief application architect at MapR Technologies, said, “In my work at Apache, I have rarely seen an incubating project build a community as well as the Apache Beam project has done. The way that they have been able to complement and enhance other streaming data projects is really a credit to everyone involved.”
The current release of Beam is 0.4.0.