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Google Cloud Datastore (Cloud Datastore) is a highly scalable, fully managed NoSQL database service offered by Google on the Google Cloud Platform. [1] Cloud Datastore is built upon Google's Bigtable and Megastore technology. [2] Google Cloud Datastore allows the user to create databases either in Native or Datastore Mode. Native Mode is ...
Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]
Google Cloud Platform is a part [8] of Google Cloud, which includes the Google Cloud Platform public cloud infrastructure, as well as Google Workspace (G Suite), enterprise versions of Android and ChromeOS, and application programming interfaces (APIs) for machine learning and enterprise mapping services.
A wide-column store (or extensible record store) is a type of NoSQL database. [1] It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table.
A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider.
Google Cloud Firestore is the successor to Google Cloud Datastore and replaces GQL with a document-based query method that treats stored objects as collections of documents. Firestore was launched in October 2017.
Data as a service (DaaS) is a cloud-based software tool used for working with data, such as managing data in a data warehouse or analyzing data with business intelligence. It is enabled by software as a service (SaaS). [ 1 ]
Examples of column-oriented formats include Apache ORC, [3] Apache Parquet, [4] Apache Arrow, [5] formats used by BigQuery, Amazon Redshift and Snowflake. Predominant examples of row-oriented formats include CSV, formats used in most relational databases , the in-memory format of Apache Spark , and Apache Avro .