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Oracle and IBM Db2 provide a construct explicitly named CLOB, [1] [2] and the majority of other database systems support some form of the concept, often labeled as text, memo or long character fields. CLOBs usually have very high size-limits, of the order of gigabytes. The tradeoff for the capacity is usually limited access methods.
To reduce such index size, some systems allow including non-key fields in the index. Non-key fields are not themselves part of the index ordering but only included at the leaf level, allowing for a covering index with less overall index size. This can be done in SQL with CREATE INDEX my_index ON my_table (id) INCLUDE (name);. [8] [9]
Max table size Max row size Max columns per row Max Blob/Clob size Max CHAR size Max NUMBER size Min DATE value Max DATE value Max column name size Informix Dynamic Server: ≈0.5 YB 12: ≈0,5YB 12: 32,765 bytes (exclusive of large objects) 32,765 4 TB 32,765 14: 10 125 13: 01/01/0001 10: 12/31/9999 128 bytes Ingres: Unlimited Unlimited 256 KB ...
Varchar fields can be of any size up to a limit, which varies by databases: an Oracle 11g database has a limit of 4000 bytes, [1] a MySQL 5.7 database has a limit of 65,535 bytes (for the entire row) [2] and Microsoft SQL Server 2008 has a limit of 8000 bytes (unless varchar(max) is used, which has a maximum storage capacity of 2 gigabytes).
The same may not be true of B-tree: B-tree requires a tree node for every approximately N rows in the table, where N is the capacity of a single node, thus the index size is large. As BRIN only requires a tuple for each block (of many rows), the index becomes sufficiently small to make the difference between disk and memory.
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 ...
Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...
Database designers can add or remove indexes without changing application logic, reducing maintenance costs as the database grows and database usage evolves. Indexes can speed up data access, but they consume space in the database, and must be updated each time the data is altered. Indexes therefore can speed data access but slow data maintenance.