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In computing, a materialized view is a database object that contains the results of a query. For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function .
ClickHouse: C++ Released in 2016 to analyze data that is updated in real time CrateDB: Java C-Store: C++ The last release of the original code was in 2006; Vertica a commercial fork, lives on. DuckDB: C++ An embeddable, in-process, column-oriented SQL OLAP RDBMS Databend Rust An elastic and reliable Serverless Data Warehouse InfluxDB: Rust Time ...
ClickHouse is an open-source column-oriented DBMS (columnar database management system) for online analytical processing (OLAP) that allows users to generate analytical reports using SQL queries in real-time. ClickHouse Inc. is headquartered in the San Francisco Bay Area with the subsidiary, ClickHouse B.V., based in Amsterdam, Netherlands.
Materialized views were introduced by Oracle Database, while IBM Db2 provides so-called "materialized query tables" (MQTs) for the same purpose. Microsoft SQL Server introduced in its 2000 version indexed views which only store a separate index from the table, but not the entire data. PostgreSQL implemented materialized views in its 9.3 release.
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14] Character strings and national character strings. CHARACTER(n) (or CHAR(n)): fixed-width n-character string, padded with spaces as needed; CHARACTER VARYING(n) (or VARCHAR(n)): variable-width string with a maximum size of n ...
A column may contain text values, numbers, or even pointers to files in the operating system. [2] Columns typically contain simple types, though some relational database systems allow columns to contain more complex data types, such as whole documents, images, or even video clips. [3] [better source needed] A column can also be called an attribute.
High-cardinality refers to columns with values that are very uncommon or unique. High-cardinality column values are typically identification numbers, email addresses, or user names. An example of a data table column with high-cardinality would be a USERS table with a column named USER_ID. This column would contain unique values of 1-n. Each ...
A nullable attribute would be in violation of condition 4, which requires every column to contain exactly one value from its column's domain. This aspect of condition 4 is controversial. It marks an important departure from Codd's later vision of the relational model, [12] which made explicit provision for nulls. [13]