As said at Datatypes In
SQLite Version 3:

Datatypes In SQLite Version 3

Most SQL database engines (every SQL database engine other than SQLite,
as far as we know) uses static, rigid typing. With static typing, the
datatype of a value is determined by its container - the particular column
in which the value is stored.

SQLite uses a more general dynamic type system. In SQLite, the datatype
of a value is associated with the value itself, not with its container.
The dynamic type system of SQLite is backwards compatible with the more
common static type systems of other database engines in the sense that SQL
statements that work on statically typed databases should work the same
way in SQLite. However, the dynamic typing in SQLite allows it to do
things which are not possible in traditional rigidly typed databases.

1.0 Storage Classes and Datatypes

Each value stored in an SQLite database (or manipulated by the database
engine) has one of the following storage classes:

• NULL. The value is a NULL value.


• INTEGER. The value is a signed integer, stored in 1,
  2, 3, 4, 6, or 8 bytes depending on the magnitude of the value.


• REAL. The value is a floating point value, stored as
  an 8-byte IEEE floating point number.


• TEXT. The value is a text string, stored using the
  database encoding (UTF-8, UTF-16BE or UTF-16LE).


• BLOB. The value is a blob of data, stored exactly as
  it was input.

Note that a storage class is slightly more general than a datatype. The
INTEGER storage class, for example, includes 6 different integer datatypes
of different lengths. This makes a difference on disk. But as soon as
INTEGER values are read off of disk and into memory for processing, they
are converted to the most general datatype (8-byte signed integer). And so
for the most part, "storage class" is indistinguishable from "datatype"
and the two terms can be used interchangeably.

Any column in an SQLite version 3 database, except an INTEGER
PRIMARY KEY column, may be used to store a value of any storage
class.

All values in SQL statements, whether they are literals embedded in SQL
statement text or parameters bound
to precompiled SQL
statements have an implicit storage class. Under circumstances
described below, the database engine may convert values between numeric
storage classes (INTEGER and REAL) and TEXT during query execution.

1.1 Boolean Datatype

SQLite does not have a separate Boolean storage class. Instead, Boolean
values are stored as integers 0 (false) and 1 (true).

1.2 Date and Time Datatype

SQLite does not have a storage class set aside for storing dates and/or
times. Instead, the built-in Date
And Time Functions of SQLite are capable of storing dates and times as
TEXT, REAL, or INTEGER values:

• TEXT as ISO8601 strings ("YYYY-MM-DD
  HH:MM:SS.SSS").


• REAL as Julian day numbers, the number of days
  since noon in Greenwich on November 24, 4714 B.C. according to the
  proleptic Gregorian calendar.


• INTEGER as Unix Time, the number of seconds since
  1970-01-01 00:00:00 UTC.

Applications can chose to store dates and times in any of these formats
and freely convert between formats using the built-in date and time
functions.

2.0 Type Affinity

In order to maximize compatibility between SQLite and other database
engines, SQLite supports the concept of "type affinity" on columns. The
type affinity of a column is the recommended type for data stored in that
column. The important idea here is that the type is recommended, not
required. Any column can still store any type of data. It is just that
some columns, given the choice, will prefer to use one storage class over
another. The preferred storage class for a column is called its
"affinity".

Each column in an SQLite 3 database is assigned one of the following
type affinities:

• TEXT


• NUMERIC


• INTEGER


• REAL


• NONE

A column with TEXT affinity stores all data using storage classes NULL,
TEXT or BLOB. If numerical data is inserted into a column with TEXT
affinity it is converted into text form before being stored.

A column with NUMERIC affinity may contain values using all five
storage classes. When text data is inserted into a NUMERIC column, the
storage class of the text is converted to INTEGER or REAL (in order of
preference) if such conversion is lossless and reversible. For conversions
between TEXT and REAL storage classes, SQLite considers the conversion to
be lossless and reversible if the first 15 significant decimal digits of
the number are preserved. If the lossless conversion of TEXT to INTEGER or
REAL is not possible then the value is stored using the TEXT storage
class. No attempt is made to convert NULL or BLOB values.

A string might look like a floating-point literal with a decimal point
and/or exponent notation but as long as the value can be expressed as an
integer, the NUMERIC affinity will convert it into an integer. Hence, the
string ‘3.0e+5‘ is stored in a column with NUMERIC affinity as the integer
300000, not as the floating point value 300000.0.

A column that uses INTEGER affinity behaves the same as a column with
NUMERIC affinity. The difference between INTEGER and NUMERIC affinity is
only evident in a CAST
expression.

A column with REAL affinity behaves like a column with NUMERIC affinity
except that it forces integer values into floating point representation.
(As an internal optimization, small floating point values with no
fractional component and stored in columns with REAL affinity are written
to disk as integers in order to take up less space and are automatically
converted back into floating point as the value is read out. This
optimization is completely invisible at the SQL level and can only be
detected by examining the raw bits of the database file.)

A column with affinity NONE does not prefer one storage class over
another and no attempt is made to coerce data from one storage class into
another.

2.1 Determination Of Column Affinity

The affinity of a column is determined by the declared type of the
column, according to the following rules in the order shown:

1. If the declared type contains the string "INT" then it is assigned
   INTEGER affinity.


2. If the declared type of the column contains any of the strings
   "CHAR", "CLOB", or "TEXT" then that column has TEXT affinity. Notice
   that the type VARCHAR contains the string "CHAR" and is thus assigned
   TEXT affinity.


3. If the declared type for a column contains the string "BLOB" or if no
   type is specified then the column has affinity NONE.


4. If the declared type for a column contains any of the strings "REAL",
   "FLOA", or "DOUB" then the column has REAL affinity.


5. Otherwise, the affinity is NUMERIC.

Note that the order of the rules for determining column affinity is
important. A column whose declared type is "CHARINT" will match both rules
1 and 2 but the first rule takes precedence and so the column affinity
will be INTEGER.

2.2 Affinity Name Examples

The following table shows how many common datatype names from more
traditional SQL implementations are converted into affinities by the five
rules of the previous section. This table shows only a small subset of the
datatype names that SQLite will accept. Note that numeric arguments in
parentheses that following the type name (ex: "VARCHAR(255)") are ignored
by SQLite - SQLite does not impose any length restrictions (other than the
large global SQLITE_MAX_LENGTH
limit) on the length of strings, BLOBs or numeric values.

Example Typenames From The CREATE TABLE Statement or CAST Expression	Resulting Affinity	Rule Used To Determine Affinity
INT INTEGER TINYINT SMALLINT MEDIUMINT BIGINT UNSIGNED BIG INT INT2 INT8	INTEGER	1
CHARACTER(20) VARCHAR(255) VARYING CHARACTER(255) NCHAR(55) NATIVE CHARACTER(70) NVARCHAR(100) TEXT CLOB	TEXT	2
BLOB no datatype specified	NONE	3
REAL DOUBLE DOUBLE PRECISION FLOAT	REAL	4
NUMERIC DECIMAL(10,5) BOOLEAN DATE DATETIME	NUMERIC	5

Note that a declared type of "FLOATING POINT" would give INTEGER
affinity, not REAL affinity, due to the "INT" at the end of "POINT". And
the declared type of "STRING" has an affinity of NUMERIC, not TEXT.

2.3 Column Affinity Behavior Example

The following SQL demonstrates how SQLite uses column affinity to do
type conversions when values are inserted into a table.

CREATE TABLE t1(

    t  TEXT,     -- text affinity by rule 2

    nu NUMERIC,  -- numeric affinity by rule 5

    i  INTEGER,  -- integer affinity by rule 1

    r  REAL,     -- real affinity by rule 4

    no BLOB      -- no affinity by rule 3

);

-- Values stored as TEXT, INTEGER, INTEGER, REAL, TEXT.

INSERT INTO t1 VALUES(‘500.0‘, ‘500.0‘, ‘500.0‘, ‘500.0‘, ‘500.0‘);

SELECT typeof(t), typeof(nu), typeof(i), typeof(r), typeof(no) FROM t1;

text|integer|integer|real|text
-- Values stored as TEXT, INTEGER, INTEGER, REAL, REAL.

DELETE FROM t1;

INSERT INTO t1 VALUES(500.0, 500.0, 500.0, 500.0, 500.0);

SELECT typeof(t), typeof(nu), typeof(i), typeof(r), typeof(no) FROM t1;

text|integer|integer|real|real
-- Values stored as TEXT, INTEGER, INTEGER, REAL, INTEGER.

DELETE FROM t1;

INSERT INTO t1 VALUES(500, 500, 500, 500, 500);

SELECT typeof(t), typeof(nu), typeof(i), typeof(r), typeof(no) FROM t1;

text|integer|integer|real|integer
-- BLOBs are always stored as BLOBs regardless of column affinity.

DELETE FROM t1;

INSERT INTO t1 VALUES(x‘0500‘, x‘0500‘, x‘0500‘, x‘0500‘, x‘0500‘);

SELECT typeof(t), typeof(nu), typeof(i), typeof(r), typeof(no) FROM t1;

blob|blob|blob|blob|blob
-- NULLs are also unaffected by affinity

DELETE FROM t1;

INSERT INTO t1 VALUES(NULL,NULL,NULL,NULL,NULL);

SELECT typeof(t), typeof(nu), typeof(i), typeof(r), typeof(no) FROM t1;

null|null|null|null|null

3.0 Comparison Expressions

SQLite version 3 has the usual set of SQL comparison operators
including "=", "==", "<", "<=", ">", ">=", "!=", "<>",
"IN", "NOT IN", "BETWEEN", "IS", and "IS NOT", .

3.1 Sort Order

The results of a comparison depend on the storage classes of the
operands, according to the following rules:

• A value with storage class NULL is considered less than any other
  value (including another value with storage class NULL).


• An INTEGER or REAL value is less than any TEXT or BLOB value. When an
  INTEGER or REAL is compared to another INTEGER or REAL, a numerical
  comparison is performed.


• A TEXT value is less than a BLOB value. When two TEXT values are
  compared an appropriate collating sequence is used to determine the
  result.


• When two BLOB values are compared, the result is determined using
  memcmp().

3.2 Affinity Of Comparison Operands

SQLite may attempt to convert values between the storage classes
INTEGER, REAL, and/or TEXT before performing a comparison. Whether or not
any conversions are attempted before the comparison takes place depends on
the affinity of the operands. Operand affinity is determined by the
following rules:

• An expression that is a simple reference to a column value has the
  same affinity as the column. Note that if X and Y.Z are column names,
  then +X and +Y.Z are considered expressions for the purpose of
  determining affinity.


• An expression of the form "CAST(expr AS type)" has
  an affinity that is the same as a column with a declared type of
  "type".


• Otherwise, an expression has NONE affinity.

3.3 Type Conversions Prior To Comparison

To "apply affinity" means to convert an operand to a particular storage
class if and only if the conversion is lossless and reversible. Affinity
is applied to operands of a comparison operator prior to the comparison
according to the following rules in the order shown:

• If one operand has INTEGER, REAL or NUMERIC affinity and the other
  operand as TEXT or NONE affinity then NUMERIC affinity is applied to
  other operand.


• If one operand has TEXT affinity and the other has NONE affinity,
  then TEXT affinity is applied to the other operand.


• Otherwise, no affinity is applied and both operands are compared as
  is.

The expression "a BETWEEN b AND c" is treated as two separate binary
comparisons "a >= b AND a <= c", even if that means different
affinities are applied to ‘a‘ in each of the comparisons. Datatype
conversions in comparisons of the form "x IN (SELECT y ...)" are handled
is if the comparison were really "x=y". The expression "a IN (x, y, z,
...)" is equivalent to "a = +x OR a = +y OR a = +z OR ...". In other
words, the values to the right of the IN operator (the "x", "y", and "z"
values in this example) are considered to have no affinity, even if they
happen to be column values or CAST expressions.

3.4 Comparison Example

CREATE TABLE t1(

    a TEXT,      -- text affinity

    b NUMERIC,   -- numeric affinity

    c BLOB,      -- no affinity

    d            -- no affinity

);

-- Values will be stored as TEXT, INTEGER, TEXT, and INTEGER respectively

INSERT INTO t1 VALUES(‘500‘, ‘500‘, ‘500‘, 500);

SELECT typeof(a), typeof(b), typeof(c), typeof(d) FROM t1;

text|integer|text|integer
-- Because column "a" has text affinity, numeric values on the

-- right-hand side of the comparisons are converted to text before

-- the comparison occurs.

SELECT a < 40,   a < 60,   a < 600 FROM t1;

0|1|1
-- Text affinity is applied to the right-hand operands but since

-- they are already TEXT this is a no-op; no conversions occur.

SELECT a < ‘40‘, a < ‘60‘, a < ‘600‘ FROM t1;

0|1|1
-- Column "b" has numeric affinity and so numeric affinity is applied

-- to the operands on the right.  Since the operands are already numeric,

-- the application of affinity is a no-op; no conversions occur.  All

-- values are compared numerically.

SELECT b < 40,   b < 60,   b < 600 FROM t1;

0|0|1
-- Numeric affinity is applied to operands on the right, converting them

-- from text to integers.  Then a numeric comparison occurs.

SELECT b < ‘40‘, b < ‘60‘, b < ‘600‘ FROM t1;

0|0|1
-- No affinity conversions occur.  Right-hand side values all have

-- storage class INTEGER which are always less than the TEXT values

-- on the left.

SELECT c < 40,   c < 60,   c < 600 FROM t1;

0|0|0
-- No affinity conversions occur.  Values are compared as TEXT.

SELECT c < ‘40‘, c < ‘60‘, c < ‘600‘ FROM t1;

0|1|1
-- No affinity conversions occur.  Right-hand side values all have

-- storage class INTEGER which compare numerically with the INTEGER

-- values on the left.

SELECT d < 40,   d < 60,   d < 600 FROM t1;

0|0|1
-- No affinity conversions occur.  INTEGER values on the left are

-- always less than TEXT values on the right.

SELECT d < ‘40‘, d < ‘60‘, d < ‘600‘ FROM t1;

1|1|1

All of the result in the example are the same if the comparisons are
commuted - if expressions of the form "a<40" are rewritten as
"40>a".

4.0 Operators

All mathematical operators (+, -, *, /, %, <<, >>, &,
and |) cast both operands to the NUMERIC storage class prior to being
carried out. The cast is carried through even if it is lossy and
irreversible. A NULL operand on a mathematical operator yields a NULL
result. An operand on a mathematical operator that does not look in any
way numeric and is not NULL is converted to 0 or 0.0.

5.0 Sorting, Grouping and Compound SELECTs

When query results are sorted by an ORDER BY clause, values with
storage class NULL come first, followed by INTEGER and REAL values
interspersed in numeric order, followed by TEXT values in collating
sequence order, and finally BLOB values in memcmp() order. No storage
class conversions occur before the sort.

When grouping values with the GROUP BY clause values with different
storage classes are considered distinct, except for INTEGER and REAL
values which are considered equal if they are numerically equal. No
affinities are applied to any values as the result of a GROUP by
clause.

The compound SELECT operators UNION, INTERSECT and EXCEPT perform
implicit comparisons between values. No affinity is applied to comparison
operands for the implicit comparisons associated with UNION, INTERSECT, or
EXCEPT - the values are compared as is.

6.0 Collating Sequences

When SQLite compares two strings, it uses a collating sequence or
collating function (two words for the same thing) to determine which
string is greater or if the two strings are equal. SQLite has three
built-in collating functions: BINARY, NOCASE, and RTRIM.

• BINARY - Compares string data using memcmp(),
  regardless of text encoding.


• NOCASE - The same as binary, except the 26 upper
  case characters of ASCII are folded to their lower case equivalents
  before the comparison is performed. Note that only ASCII characters are
  case folded. SQLite does not attempt to do full UTF case folding due to
  the size of the tables required.


• RTRIM - The same as binary, except that trailing
  space characters are ignored.

An application can register additional collating functions using the sqlite3_create_collation()
interface.

6.1 Assigning Collating Sequences from SQL

Every column of every table has an associated collating function. If no
collating function is explicitly defined, then the collating function
defaults to BINARY. The COLLATE clause of the column
definition is used to define alternative collating functions for a
column.

The rules for determining which collating function to use for a binary
comparison operator (=, <, >, <=, >=, !=, IS, and IS NOT) are
as follows and in the order shown:

1. If either operand has an explicit collating function assignment using
   the postfix COLLATE
   operator, then the explicit collating function is used for
   comparison, with precedence to the collating function of the left
   operand.


2. If either operand is a column, then the collating function of that
   column is used with precedence to the left operand. For the purposes of
   the previous sentence, a column name preceded by one or more unary "+"
   operators is still considered a column name.


3. Otherwise, the BINARY collating function is used for comparison.

An operand of a comparison is considered to have an explicit collating
function assignment (rule 1 above) if any subexpression of the operand
uses the postfix COLLATE
operator. Thus, if a COLLATE
operator is used anywhere in a comparision expression, the collating
function defined by that operator is used for string comparison regardless
of what table columns might be a part of that expression. If two or more
COLLATE
operator subexpressions appear anywhere in a comparison, the left most
explicit collating function is used regardless of how deeply the COLLATE
operators are nested in the expression and regardless of how the
expression is parenthesized.

The expression "x BETWEEN y and z" is logically equivalent to two
comparisons "x >= y AND x <= z" and works with respect to collating
functions as if it were two separate comparisons. The expression "x IN
(SELECT y ...)" is handled in the same way as the expression "x = y" for
the purposes of determining the collating sequence. The collating sequence
used for expressions of the form "x IN (y, z, ...)" is the collating
sequence of x.

Terms of the ORDER BY clause that is part of a SELECT
statement may be assigned a collating sequence using the COLLATE
operator, in which case the specified collating function is used for
sorting. Otherwise, if the expression sorted by an ORDER BY clause is a
column, then the collating sequence of the column is used to determine
sort order. If the expression is not a column and has no COLLATE clause,
then the BINARY collating sequence is used.

6.2 Collation Sequence Examples

The examples below identify the collating sequences that would be used
to determine the results of text comparisons that may be performed by
various SQL statements. Note that a text comparison may not be required,
and no collating sequence used, in the case of numeric, blob or NULL
values.

CREATE TABLE t1(

    x INTEGER PRIMARY KEY,

    a,                 /* collating sequence BINARY */

    b COLLATE BINARY,  /* collating sequence BINARY */

    c COLLATE RTRIM,   /* collating sequence RTRIM  */

    d COLLATE NOCASE   /* collating sequence NOCASE */

);

                   /* x   a     b     c       d */

INSERT INTO t1 VALUES(1,‘abc‘,‘abc‘, ‘abc  ‘,‘abc‘);

INSERT INTO t1 VALUES(2,‘abc‘,‘abc‘, ‘abc‘,  ‘ABC‘);

INSERT INTO t1 VALUES(3,‘abc‘,‘abc‘, ‘abc ‘, ‘Abc‘);

INSERT INTO t1 VALUES(4,‘abc‘,‘abc ‘,‘ABC‘,  ‘abc‘);

/* Text comparison a=b is performed using the BINARY collating sequence. */

SELECT x FROM t1 WHERE a = b ORDER BY x;

--result 1 2 3
/* Text comparison a=b is performed using the RTRIM collating sequence. */

SELECT x FROM t1 WHERE a = b COLLATE RTRIM ORDER BY x;

--result 1 2 3 4
/* Text comparison d=a is performed using the NOCASE collating sequence. */

SELECT x FROM t1 WHERE d = a ORDER BY x;

--result 1 2 3 4
/* Text comparison a=d is performed using the BINARY collating sequence. */

SELECT x FROM t1 WHERE a = d ORDER BY x;

--result 1 4
/* Text comparison ‘abc‘=c is performed using the RTRIM collating sequence. */

SELECT x FROM t1 WHERE ‘abc‘ = c ORDER BY x;

--result 1 2 3
/* Text comparison c=‘abc‘ is performed using the RTRIM collating sequence. */

SELECT x FROM t1 WHERE c = ‘abc‘ ORDER BY x;

--result 1 2 3
/* Grouping is performed using the NOCASE collating sequence (Values

** ‘abc‘, ‘ABC‘, and ‘Abc‘ are placed in the same group). */

SELECT count(*) FROM t1 GROUP BY d ORDER BY 1;

--result 4
/* Grouping is performed using the BINARY collating sequence.  ‘abc‘ and

** ‘ABC‘ and ‘Abc‘ form different groups */

SELECT count(*) FROM t1 GROUP BY (d || ‘‘) ORDER BY 1;

--result 1 1 2
/* Sorting or column c is performed using the RTRIM collating sequence. */

SELECT x FROM t1 ORDER BY c, x;

--result 4 1 2 3
/* Sorting of (c||‘‘) is performed using the BINARY collating sequence. */

SELECT x FROM t1 ORDER BY (c||‘‘), x;

--result 4 2 3 1
/* Sorting of column c is performed using the NOCASE collating sequence. */

SELECT x FROM t1 ORDER BY c COLLATE NOCASE, x;

--result 2 4 3 1

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