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Bigtable is one of the prototypical examples of a wide-column store. It maps two arbitrary string values (row key and column key) and timestamp (hence three-dimensional mapping) into an associated arbitrary byte array. It is not a relational database and can be better defined as a sparse, distributed multi-dimensional sorted map.
NoSQL database Yes, Hybrid DRAM and flash for persistence Yes Yes, Distributed for scale Yes Yes C (small bits of assembly language) Aerospike AGPL v3: AllegroGraph: Graph database: Yes No - v5, 2010 Yes Yes No Common Lisp: Franz Inc. Proprietary: Apache Ignite: Key-value To and from an underlying persistent storage (e.g. an RDBMS) Yes Yes Yes ...
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]
Yes - user manager with support for database and schema permissions as well as for individual object (table, view, functions) permissions; Some - simple user manager with support for database and schema permissions; No - no user manager, or read-only user manager
A database management system (DBMS) is a computer program (or more typically, a suite of them) designed to manage a database, a large set of structured data, and run operations on the data requested by numerous users.
An SQL schema is simply a namespace within a database; things within this namespace are addressed using the member operator dot ". This seems to be a universal among all of the implementations. A true fully (database, schema, and table) qualified query is exemplified as such: SELECT * FROM database . schema . table
The product was the first commercially available business intelligence platform built for and aimed at scalable or massively parallel relational database management systems like Amazon Redshift, Google BigQuery, HP Vertica, Netezza, and Teradata.
Database scalability is the ability of a database to handle changing demands by adding/removing resources. Databases use a host of techniques to cope. [ 1 ] According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant."