LIKE和=是不同的。LIKE是在搜索查询中使用的。它还允许像_(简单字符通配符)和%(多字符通配符)这样的通配符。

如果你想要精确匹配，应该使用=，它会更快。

这个网站解释了LIKE

如果要搜索精确匹配，可以同时使用，=和LIKE。

在这种情况下，使用“=”稍微快一点(搜索精确匹配)——你可以自己检查，在SQL Server Management Studio中进行两次相同的查询，一次使用“=”，一次使用“LIKE”，然后使用“查询”/“包括实际执行计划”。

执行这两个查询，您应该会看到两次结果，以及两个实际的执行计划。在我的例子中，它们被分割成50%对50%，但是“=”执行计划有一个更小的“估计子树成本”(当你将鼠标悬停在最左边的“SELECT”框上时显示)-但是，这真的不是一个巨大的差异。

但是当你开始在LIKE表达式中使用通配符进行搜索时，搜索性能将会下降。搜索“LIKE Mill%”仍然可以相当快- SQL Server可以使用该列的索引，如果有一个。搜索“LIKE %expression%”非常慢，因为SQL Server能够满足此搜索的唯一方法是执行全表扫描。所以点赞时要小心!

Marc

使用=可以避免在运行时构建查询时字符串中的通配符和特殊字符冲突。

这使程序员的工作更轻松，因为不必转义所有可能滑入LIKE子句并不能产生预期结果的特殊通配符。毕竟，=是99%的用例场景，每次都必须逃避它们将是一种痛苦。

在90年代翻白眼

我也怀疑它有点慢，但如果模式中没有通配符，我怀疑它的意义。

除了通配符，=和LIKE之间的区别还取决于SQL服务器的类型和列类型。

举个例子:

CREATE TABLE testtable (
  varchar_name VARCHAR(10),
  char_name CHAR(10),
  val INTEGER
);

INSERT INTO testtable(varchar_name, char_name, val)
    VALUES ('A', 'A', 10), ('B', 'B', 20);

SELECT 'VarChar Eq Without Space', val FROM testtable WHERE varchar_name='A'
UNION ALL
SELECT 'VarChar Eq With Space', val FROM testtable WHERE varchar_name='A '
UNION ALL
SELECT 'VarChar Like Without Space', val FROM testtable WHERE varchar_name LIKE 'A'
UNION ALL
SELECT 'VarChar Like Space', val FROM testtable WHERE varchar_name LIKE 'A '
UNION ALL
SELECT 'Char Eq Without Space', val FROM testtable WHERE char_name='A'
UNION ALL
SELECT 'Char Eq With Space', val FROM testtable WHERE char_name='A '
UNION ALL
SELECT 'Char Like Without Space', val FROM testtable WHERE char_name LIKE 'A'
UNION ALL
SELECT 'Char Like With Space', val FROM testtable WHERE char_name LIKE 'A '

Using MS SQL Server 2012, the trailing spaces will be ignored in the comparison, except with LIKE when the column type is VARCHAR. Using MySQL 5.5, the trailing spaces will be ignored for =, but not for LIKE, both with CHAR and VARCHAR. Using PostgreSQL 9.1, spaces are significant with both = and LIKE using VARCHAR, but not with CHAR (see documentation). The behaviour with LIKE also differs with CHAR. Using the same data as above, using an explicit CAST on the column name also makes a difference: SELECT 'CAST none', val FROM testtable WHERE char_name LIKE 'A' UNION ALL SELECT 'CAST both', val FROM testtable WHERE CAST(char_name AS CHAR) LIKE CAST('A' AS CHAR) UNION ALL SELECT 'CAST col', val FROM testtable WHERE CAST(char_name AS CHAR) LIKE 'A' UNION ALL SELECT 'CAST value', val FROM testtable WHERE char_name LIKE CAST('A' AS CHAR) This only returns rows for "CAST both" and "CAST col".

=比LIKE快得多。

在有11GB数据和超过1000万条记录的MySQL上测试，f_time列被索引了。

SELECT * FROM XXXXX WHERE f_time = '1621442261' -花费0.00s并返回330条记录

SELECT * FROM XXXXX WHERE f_time like '1621442261' -花费44.71秒并返回330条记录

要解决最初关于性能的问题，可以归结为索引利用率。当进行简单的表扫描时，“LIKE”和“=”是相同的。当涉及到索引时，这取决于LIKE子句是如何形成的。更具体地说，通配符的位置是什么?

考虑以下几点:

CREATE TABLE test(
    txt_col  varchar(10) NOT NULL
)
go

insert test (txt_col)
select CONVERT(varchar(10), row_number() over (order by (select 1))) r
  from master..spt_values a, master..spt_values b
go

CREATE INDEX IX_test_data 
    ON test (txt_col);
go 

--Turn on Show Execution Plan
set statistics io on

--A LIKE Clause with a wildcard at the beginning
DBCC DROPCLEANBUFFERS
SELECT txt_Col from test where txt_col like '%10000'
--Results in
--Table 'test'. Scan count 3, logical reads 15404, physical reads 2, read-ahead reads 15416, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
--Index SCAN is 85% of Query Cost

--A LIKE Clause with a wildcard in the middle
DBCC DROPCLEANBUFFERS
SELECT txt_Col from test where txt_col like '1%99'
--Results in
--Table 'test'. Scan count 1, logical reads 3023, physical reads 3, read-ahead reads 3018, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
--Index Seek is 100% of Query Cost for test data, but it may result in a Table Scan depending on table size/structure

--A LIKE Clause with no wildcards
DBCC DROPCLEANBUFFERS
SELECT txt_Col from test where txt_col like '10000'
--Results in
--Table 'test'. Scan count 1, logical reads 3, physical reads 2, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
--Index Seek is 100% of Query Cost
GO

--an "=" clause = does Index Seek same as above
DBCC DROPCLEANBUFFERS
SELECT txt_Col from test where txt_col = '10000'
--Results in
--Table 'test'. Scan count 1, logical reads 3, physical reads 2, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.
--Index Seek is 100% of Query Cost
GO


DROP TABLE test

当使用"="和"LIKE"时，在查询计划的创建中也可能存在可以忽略不计的差异。