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Google Drive is a service for users to store and share their private files. Google Drive is intended for use by individuals, and has a UI that offers many features for creating, editing and sharing your work, in addition to uploading files for storage.
Google Drive enables users to access and manage all their file content in the Google’s cloud and have it accessible from anywhere. While Google Drive provides an API for uploading files and for searching and retrieving stored items, the UI is intended to be the primary mechanism for interaction. If your application is working with files that have historically been stored locally on a user’s computer or phone, Google Drive is a good option.
Google Cloud Storage
Google Cloud Storage is a service for storing and accessing data in Google’s cloud. It is primarily intended for programmatic use within applications. It has a interactive UI, which is helpful for learning about the product, getting started using it, and quickly uploading or deleting content.
Google Cloud Storage offers direct access to Google’s scalable storage and networking infrastructure, as well as powerful authentication and data sharing mechanisms. It lets you store files of any size and manage access to your data on an individual or group basis.
Data stored in Google Cloud Storage can be designated as public or private. Public data can be shared with anyone, enabling you to use Google Cloud Storage as a conduit to making selected parts of your data available outside your company.
Google Cloud SQL
Google Cloud SQL allows you to create, configure, and use MySQL databases that live in Google’s cloud. It is a fully-managed service that maintains, manages, and administers your databases.
Google Cloud SQL is primarily intended for programmatic use within applications. It has an interactive UI, which is helpful for learning about the product, getting started using it, investigating the schema, and submitting trial queries.
Google BigQuery Service is a massively parallel query datastore that allows you to run SQL-like queries against very large datasets, with potentially billions of rows, in a matter of seconds. It is primarily intended for programmatic use within applications. It provides an interactive UI, which is helpful for learning about the product and running interactive queries.
BigQuery is ideal for running queries over vast amounts of data —up to billions of rows— in seconds. It is good for analyzing vast quantities of data quickly, but not for modifying it. In data analysis terms, BigQuery is an OLAP (online analytical processing) system, and works best for interactive analysis of very large datasets, typically using a small number of very large, append-only tables.
BigQuery is append-only, so you can’t update or change data that is already in a BigQuery table, wherease with Google Cloud SQL, you have full control over changing the data in the tables.
The Datastore is a NoSQL (non-relational) key/value store that supports unlimited scaling. You can store any key/value pairs you want; entities stored in the Datastore do not need to conform to the same structure. The Datastore stores the data on Google’s infrastructure.
You can also use the Memcache service to keep data values in the cache to reduce hits to the datastore.
The Cloud Datastore and Google Cloud SQL can be used to store the same kind of application data in general, but the datastore uses schemaless, NoSQL data while Google Cloud SQL stores data in MySQL tables.
TheCloud Datastore provides NoSQL key-value storage that is highly scalable. Google Cloud SQL supports complex queries and ACID transactions, but this means the database acts as a ‘fixed pipe’ and performance is less scalable. The decision likely comes down to whether you are more comfortable with traditional SQL with tightly-managed schema, or NoSQL where there are no requirements of conformity across objects of the same kind. Many applications use both types of storage.