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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 ...
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 wide-column store can be interpreted as a two-dimensional key–value store. [1] Google's Bigtable is one of the prototypical examples of a wide-column store. [2]
BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service that supports querying using a dialect of SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011. [1]
A data store is a repository for persistently storing and managing collections of data which include not just repositories like databases, but also simpler store types such as simple files, emails, etc. [1]
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.
Dremel is a distributed system developed at Google for interactively querying large datasets.. Dremel is the query engine used in Google's BigQuery service. [1]Dremel is the inspiration for Apache Drill, [2] Apache Impala, [3] and Dremio, [4] an Apache licensed platform that includes a distributed SQL execution engine.
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 .
The central concept of a document-oriented database is the notion of a document.While each document-oriented database implementation differs on the details of this definition, in general, they all assume documents encapsulate and encode data (or information) in some standard format or encoding.