Which cloud service is best suited for integrating and analyzing multiple datasets in real-time?

BigQuery is the most suitable cloud service for integrating and analyzing multiple datasets in real-time due to its powerful capabilities in handling large-scale data analytics. It is a fully managed, serverless data warehouse solution designed for processing and querying massive datasets quickly using SQL-like syntax. BigQuery's architecture allows it to perform fast and efficient analytical queries on diverse datasets, making it ideal for organizations that need to analyze real-time data from various sources.

The integration capability of BigQuery is enhanced with features like federated queries, which allow data analysis across different sources without the need to move the data, and its seamless connection with other Google Cloud services. This makes it a strong candidate for real-time analytics and reporting, enabling users to derive insights and make data-driven decisions almost instantly from various datasets.

In contrast, while Data Fusion offers integration of data from different sources and can be used for data preparation and transformation, it does not inherently provide the same level of real-time analytics capabilities that BigQuery does. App Engine serves primarily as a platform for developing and deploying applications, rather than focusing on data analysis. Cloud Pub/Sub is excellent for event-driven architectures and real-time messaging between applications but does not directly facilitate data analysis or complex querying of datasets. Therefore, BigQuery stands out