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ClickHouse was designed for OLAP queries. [5] ClickHouse performs well when: It works with a small number of tables that contain a large number of columns. Queries use a large number of rows extracted from the DB, but only a small subset of columns. Queries are relatively rare (usually around 100 requests per second per server).
In relational databases, the information schema (information_schema) is an ANSI-standard set of read-only views that provide information about all of the tables, views, columns, and procedures in a database. [1]
ClickHouse: Apache License 2.0 Clustrix: Proprietary CockroachDB: Proprietary CSQL: Proprietary CUBRID: Apache, BSD DataEase: Proprietary DataFlex: Proprietary Dataphor: Proprietary dBase: Proprietary Derby (aka Java DB) Apache License 2.0 Empress Embedded Database: Proprietary EnterpriseDB: Proprietary eXtremeDB: Proprietary Exasol ...
These items are related to a popular animated show. 4. This category is related to parts of a classic four-word phrase/song (hint: look closely at the beginning of each word).
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
The term "schema" refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database.
The cube metadata is typically created from a star schema or snowflake schema or fact constellation of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables. Each measure can be thought of as having a set of labels, or meta-data associated with it.
Oracle Database provides information about all of the tables, views, columns, and procedures in a database. This information about information is known as metadata. [1] It is stored in two locations: data dictionary tables (accessed via built-in views) and a metadata registry.