You will distribute financial market data as: real-time event stream, ANSI SQL access to real-time and historical data, and batch historical exports. Which combination of GCP services provides these capabilities?

This combination directly addresses all requirements. Cloud Pub/Sub provides a real-time event stream for market data. BigQuery offers ANSI SQL access to both real-time (via streaming inserts) and historical data, excelling in analytical queries. Cloud Storage is ideal for batch historical exports due to its scalability and cost-effectiveness for large data volumes. Cloud Dataflow, Cloud SQL, Cloud Spanner: Cloud Spanner is overkill and expensive for simple ANSI SQL access to historical data, and Cloud SQL is not designed for petabyte-scale analytics. Cloud Dataproc, Cloud Dataflow, BigQuery: Cloud Dataproc is for Hadoop/Spark workloads, not a primary real-time streaming service, and it doesn't directly provide batch export storage as efficiently as Cloud Storage. Cloud Pub/Sub, Cloud Dataproc, Cloud SQL: Cloud SQL is not suitable for large-scale historical data analytics, and Cloud Dataproc doesn't fulfill the batch export requirement as effectively as Cloud Storage.