In order to compete with Cloud giants such as Amazon, IBM, and Microsoft, Google has created two new cloud services, Cloud Dataflow and Cloud Pub/Sub, to handle Big Data necessities. Cloud Dataflow will perform very complex computations on large amounts of data in either batches or streaming mode. Cloud Pub/Sub may send and receive data from applications in a message form.

Cloud Dataflow product manager Eric Schmidt and Cloud Pub/Sub product manager Rohit Khare have written in a blog post, “These fully-managed services remove the operational burden found in traditional data processing system. They enable you to build applications on a platform that can scale with the growth of your business and drive down data processing latency, all while processing your data efficiently and reliably. Every day, customers use Google Cloud Platform to execute business-critical big data processing workloads, including: financial fraud detection, genomics analysis, inventory management, click-stream analysis, A/B user interaction testing and cloud-scale ETL.”
The authors have described Cloud Dataflow as “specifically designed to remove the complexity of developing separate systems for batch and streaming data sources by providing a unified programming model.” This program was based on previous Google innovations such as MapReduce, FlumeJava, and Millwheel.
Cloud Pub/Sub “addresses a broad range of scenarios with a single API, a managed service that eliminates those tradeoffs, and remains cost-effective as you grow, with pricing as low as 5¢ per million message operations for sustained usage.”

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