In the context of designing a scalable and cost-effective data processing solution on Google Cloud, you are tasked with processing large volumes of data that includes both historical batch data and real-time streaming data. The solution must minimize operational complexity and infrastructure costs while ensuring high availability and scalability. Considering these requirements, how does Google Cloud Dataflow optimally support both batch and streaming data processing? Choose the best option.