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Data is accessed in different ways. Online transaction processing systems often query for specific records using a set of filtering parameters. For example, an e-commerce application may need to look up a customer shipping address from a data store table that holds tens of thousands of addresses. Databases, like Cloud SQL and Cloud Datastore, provide that kind of query functionality.

In another example, a machine learning pipeline might begin by accessing files with thousands of rows of data that is used for training the model. Since machine learning models are often trained in batch mode, all of the training data is needed. Cloud Storage is a good option for storing data that is accessed in bulk.

If you need to access files using filesystem operations, then Cloud Filestore is a good option.