SQL 'Like' VS '=' Performance

SQL 'like' vs '=' performance

See https://web.archive.org/web/20150209022016/http://myitforum.com/cs2/blogs/jnelson/archive/2007/11/16/108354.aspx

Quote from there:

the rules for index usage with LIKE
are loosely like this:

If your filter criteria uses equals =
and the field is indexed, then most
likely it will use an INDEX/CLUSTERED
INDEX SEEK

If your filter criteria uses LIKE,
with no wildcards (like if you had a
parameter in a web report that COULD
have a % but you instead use the full
string), it is about as likely as #1
to use the index. The increased cost
is almost nothing.

If your filter criteria uses LIKE, but
with a wildcard at the beginning (as
in Name0 LIKE '%UTER') it's much less
likely to use the index, but it still
may at least perform an INDEX SCAN on
a full or partial range of the index.

HOWEVER, if your filter criteria uses
LIKE, but starts with a STRING FIRST
and has wildcards somewhere AFTER that
(as in Name0 LIKE 'COMP%ER'), then SQL
may just use an INDEX SEEK to quickly
find rows that have the same first
starting characters, and then look
through those rows for an exact match.

(Also keep in mind, the SQL engine
still might not use an index the way
you're expecting, depending on what
else is going on in your query and
what tables you're joining to. The
SQL engine reserves the right to
rewrite your query a little to get the
data in a way that it thinks is most
efficient and that may include an
INDEX SCAN instead of an INDEX SEEK)

SQL efficiency - [=] vs [in] vs [like] vs [matches]

I will add to that also exists and subquery.

But the performance depends on the optimizer of the given SQL engine.

In oracle you have a lot of differences between IN and EXISTS, but not necessarily in SQL Server.

The other thing that you have to consider is the selectivity of the column that you use. Some cases show that IN is better.

But you have to remember that IN is non-sargable (non search argument able) so it will not use the index to resolve the query, the LIKE and = are sargable and support the index

The best ? You should spend some time to test it in your environment

Equals(=) vs. LIKE

Different Operators

LIKE and = are different operators. Most answers here focus on the wildcard support, which is not the only difference between these operators!

= is a comparison operator that operates on numbers and strings. When comparing strings, the comparison operator compares whole strings.

LIKE is a string operator that compares character by character.

To complicate matters, both operators use a collation which can have important effects on the result of the comparison.

Motivating Example

Let us first identify an example where these operators produce obviously different results. Allow me to quote from the MySQL manual:

Per the SQL standard, LIKE performs matching on a per-character basis, thus it can produce results different from the = comparison operator:

mysql> SELECT 'ä' LIKE 'ae' COLLATE latin1_german2_ci;
+-----------------------------------------+
| 'ä' LIKE 'ae' COLLATE latin1_german2_ci |
+-----------------------------------------+
|                                       0 |
+-----------------------------------------+
mysql> SELECT 'ä' = 'ae' COLLATE latin1_german2_ci;
+--------------------------------------+
| 'ä' = 'ae' COLLATE latin1_german2_ci |
+--------------------------------------+
|                                    1 |
+--------------------------------------+

Please note that this page of the MySQL manual is called String Comparison Functions, and = is not discussed, which implies that = is not strictly a string comparison function.

How Does `=` Work?

The SQL Standard § 8.2 describes how = compares strings:

The comparison of two character strings is determined as follows:
a) If the length in characters of X is not equal to the length
in characters of Y, then the shorter string is effectively
replaced, for the purposes of comparison, with a copy of
itself that has been extended to the length of the longer
string by concatenation on the right of one or more pad
characters, where the pad character is chosen based on CS. If
CS has the NO PAD attribute, then the pad character is an
implementation-dependent character different from any
character in the character set of X and Y that collates less
than any string under CS. Otherwise, the pad character is a
.
b) The result of the comparison of X and Y is given by the
collating sequence CS.
c) Depending on the collating sequence, two strings may
compare as equal even if they are of different lengths or
contain different sequences of characters. When the operations
MAX, MIN, DISTINCT, references to a grouping column, and the
UNION, EXCEPT, and INTERSECT operators refer to character
strings, the specific value selected by these operations from
a set of such equal values is implementation-dependent.

(Emphasis added.)

What does this mean? It means that when comparing strings, the = operator is just a thin wrapper around the current collation. A collation is a library that has various rules for comparing strings. Here is an example of a binary collation from MySQL:

static int my_strnncoll_binary(const CHARSET_INFO *cs __attribute__((unused)),
                               const uchar *s, size_t slen,
                               const uchar *t, size_t tlen,
                               my_bool t_is_prefix)
{
  size_t len= MY_MIN(slen,tlen);
  int cmp= memcmp(s,t,len);
  return cmp ? cmp : (int)((t_is_prefix ? len : slen) - tlen);
}

This particular collation happens to compare byte-by-byte (which is why it's called "binary" — it doesn't give any special meaning to strings). Other collations may provide more advanced comparisons.

For example, here is a UTF-8 collation that supports case-insensitive comparisons. The code is too long to paste here, but go to that link and read the body of my_strnncollsp_utf8mb4(). This collation can process multiple bytes at a time and it can apply various transforms (such as case insensitive comparison). The = operator is completely abstracted from the vagaries of the collation.

How Does `LIKE` Work?

The SQL Standard § 8.5 describes how LIKE compares strings:

The
M LIKE P
is true if there exists a partitioning of M into substrings
such that:
i) A substring of M is a sequence of 0 or more contiguous
s of M and each representation> of M is part of exactly one substring.
ii) If the i-th substring specifier of P is an arbitrary
character specifier, the i-th substring of M is any single
.
iii) If the i-th substring specifier of P is an arbitrary string
specifier, then the i-th substring of M is any sequence of
0 or more s.
iv) If the i-th substring specifier of P is neither an
arbitrary character specifier nor an arbitrary string specifier,
then the i-th substring of M is equal to that substring
specifier according to the collating sequence of
the , without the appending of
characters to M, and has the same length as that substring
specifier.
v) The number of substrings of M is equal to the number of
substring specifiers of P.

(Emphasis added.)

This is pretty wordy, so let's break it down. Items ii and iii refer to the wildcards _ and %, respectively. If P does not contain any wildcards, then only item iv applies. This is the case of interest posed by the OP.

In this case, it compares each "substring" (individual characters) in M against each substring in P using the current collation.

Conclusions

The bottom line is that when comparing strings, = compares the entire string while LIKE compares one character at a time. Both comparisons use the current collation. This difference leads to different results in some cases, as evidenced in the first example in this post.

Which one should you use? Nobody can tell you that — you need to use the one that's correct for your use case. Don't prematurely optimize by switching comparison operators.

Any performance impact in Oracle for using LIKE 'string' vs = 'string'?

There is a clear difference when you use bind variables, which you should be using in Oracle for anything other than data warehousing or other bulk data operations.

Take the case of:

SELECT * FROM SOME_TABLE WHERE SOME_FIELD LIKE :b1

Oracle cannot know that the value of :b1 is '%some_value%', or 'some_value' etc. until execution time, so it will make an estimation of the cardinality of the result based on heuristics and come up with an appropriate plan that either may or may not be suitable for various values of :b, such as '%A','%', 'A' etc.

Similar issues can apply with an equality predicate but the range of cardinalities that might result is much more easily estimated based on column statistics or the presence of a unique constraint, for example.

So, personally I wouldn't start using LIKE as a replacement for =. The optimizer is pretty easy to fool sometimes.

SQL: like v. equals performance comparison

Assuming that both queries return the same set of rows (i.e. the list of items that you supply in the IN expression is exhaustive) you should expect almost identical performance, perhaps with some advantage for the LIKE query.

RDBMS engines have been using index searches for begins-with LIKE queries, so LIKE 'T40%' will produce records after an index search
Your IN query would be optimized for index search as well, perhaps giving RDBMS a tighter lower and upper bounds. However, there would be an additional filtering step to eliminate records outside your IN list, which is a waste of CPU cycles under the assumption that all rows would be returned anyway.

In case you'd parameterize your query, the second query becomes harder to pass to an RDBMS from your host program. All other things being equal, I would use LIKE.

Using LIKE vs. = for exact string match

I would say that the = comparator would be faster. The lexical doesn't send the comparison to another lexical system to do general matches. Instead the engine is able to just match or move on. Our db at work has millions of rows and an = is always faster.

Performance differences between equal (=) and IN with one literal value

There is no difference between those two statements, and the optimiser will transform the IN to the = when IN has just one element in it.

Though when you have a question like this, just run both statements, run their execution plan and see the differences. Here - you won't find any.

After a big search online, I found a document on SQL to support this (I assume it applies to all DBMS):

If there is only one value inside the parenthesis, this commend [sic] is equivalent to,
WHERE "column_name" = 'value1

Here is the execution plan of both queries in Oracle (most DBMS will process this the same):

EXPLAIN PLAN FOR
select * from dim_employees t
where t.identity_number = '123456789'

Plan hash value: 2312174735
-----------------------------------------------------
| Id  | Operation                   | Name          |
-----------------------------------------------------
|   0 | SELECT STATEMENT            |               |
|   1 |  TABLE ACCESS BY INDEX ROWID| DIM_EMPLOYEES |
|   2 |   INDEX UNIQUE SCAN         | SYS_C0029838  |
-----------------------------------------------------

And for IN() :

EXPLAIN PLAN FOR
select * from dim_employees t
where t.identity_number in('123456789');

Plan hash value: 2312174735
-----------------------------------------------------
| Id  | Operation                   | Name          |
-----------------------------------------------------
|   0 | SELECT STATEMENT            |               |
|   1 |  TABLE ACCESS BY INDEX ROWID| DIM_EMPLOYEES |
|   2 |   INDEX UNIQUE SCAN         | SYS_C0029838  |
-----------------------------------------------------

As you can see, both are identical. This is on an indexed column. Same goes for an unindexed column (just full table scan).

Performance of like '%Query%' vs full text search CONTAINS query

Full Text Searching (using the CONTAINS) will be faster/more efficient than using LIKE with wildcarding. Full Text Searching (FTS) includes the ability to define Full Text Indexes, which FTS can use. I don't know why you wouldn't define a FTS index if you intended to use the functionality.

LIKE with wildcarding on the left side (IE: LIKE '%Search') can not use an index (assuming one exists for the column), guaranteeing a table scan. I haven't tested & compared, but regex has the same pitfall. To clarify, LIKE '%Search' and LIKE '%Search%' can not use an index; LIKE 'Search%' can use an index.

IN vs OR in the SQL WHERE clause

I assume you want to know the performance difference between the following:

WHERE foo IN ('a', 'b', 'c')
WHERE foo = 'a' OR foo = 'b' OR foo = 'c'

According to the manual for MySQL if the values are constant IN sorts the list and then uses a binary search. I would imagine that OR evaluates them one by one in no particular order. So IN is faster in some circumstances.

The best way to know is to profile both on your database with your specific data to see which is faster.

I tried both on a MySQL with 1000000 rows. When the column is indexed there is no discernable difference in performance - both are nearly instant. When the column is not indexed I got these results:

SELECT COUNT(*) FROM t_inner WHERE val IN (1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000);
1 row fetched in 0.0032 (1.2679 seconds)

SELECT COUNT(*) FROM t_inner WHERE val = 1000 OR val = 2000 OR val = 3000 OR val = 4000 OR val = 5000 OR val = 6000 OR val = 7000 OR val = 8000 OR val = 9000;
1 row fetched in 0.0026 (1.7385 seconds)

So in this case the method using OR is about 30% slower. Adding more terms makes the difference larger. Results may vary on other databases and on other data.

SQL LIKE with no wildcards the same as '='?

As @ocdecio says, if the optimizer is smart enough there should be no difference, but if you want to make sure about what is happening behind the scenes you should compare the two query's execution plans.

SQL 'Like' VS '=' Performance