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Apache Beam is an open source unified programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing. [2] Beam Pipelines are defined using one of the provided SDKs and executed in one of the Beam’s supported runners (distributed processing back-ends) including Apache Flink, Apache Samza, Apache Spark, and Google Cloud Dataflow.
Google Cloud Dataflow was announced in June, 2014 [3] and released to the general public as an open beta in April, 2015. [4] In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs (data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. [5]
Google Compute Engine (GCE) is the infrastructure as a service (IaaS) component of Google Cloud Platform which is built on the global infrastructure that runs Google's search engine, Gmail, YouTube and other services.
Google Cloud Platform (GCP) is a suite of cloud computing services offered by Google that provides a series of modular cloud services including computing, data storage, data analytics, and machine learning, alongside a set of management tools. [5]
SDK version 1.2.2 added support for bulk downloads of data using Python. [9] App Engine's integrated Google Cloud Datastore database has a SQL-like syntax called "GQL" (Google Query Language). GQL does not support the join statement. [10] Instead, one-to-many and many-to-many relationships can be accomplished using ReferenceProperty(). [11]
Apache Beam “provides an advanced unified programming model, allowing (a developer) to implement batch and streaming data processing jobs that can run on any execution engine.” [23] The Apache Flink-on-Beam runner is the most feature-rich according to a capability matrix maintained by the Beam community.
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Apache Airflow is an open-source workflow management platform for data engineering pipelines. It started at Airbnb in October 2014 [ 2 ] as a solution to manage the company's increasingly complex workflows.