Performance Comparison of Auto‑Increment, UUID, and Random Keys in MySQL
This article investigates why MySQL recommends auto_increment over UUID or non‑sequential snowflake IDs by creating three tables, running insert and query benchmarks with Spring Boot and JdbcTemplate, analyzing index structures, and summarizing the performance trade‑offs and security considerations of each primary‑key strategy.
MySQL officially recommends using auto_increment primary keys instead of UUIDs or non‑sequential snowflake IDs; this article explores the reasons behind that recommendation through practical experiments.
Experiment Setup : Three tables— user_auto_key (auto_increment), user_uuid (UUID primary key), and user_random_key (snowflake‑generated long)—were created with identical non‑key columns. Using Spring Boot, JdbcTemplate, JUnit, and Hutool, the author inserted the same volume of randomly generated data into each table and measured insertion time with a StopWatch.
Key Code :
package com.wyq.mysqldemo;
import cn.hutool.core.collection.CollectionUtil;
import com.wyq.mysqldemo.databaseobject.UserKeyAuto;
import com.wyq.mysqldemo.databaseobject.UserKeyRandom;
import com.wyq.mysqldemo.databaseobject.UserKeyUUID;
import com.wyq.mysqldemo.diffkeytest.AutoKeyTableService;
import com.wyq.mysqldemo.diffkeytest.RandomKeyTableService;
import com.wyq.mysqldemo.diffkeytest.UUIDKeyTableService;
import com.wyq.mysqldemo.util.JdbcTemplateService;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.util.StopWatch;
import java.util.List;
@SpringBootTest
class MysqlDemoApplicationTests {
@Autowired
private JdbcTemplateService jdbcTemplateService;
@Autowired
private AutoKeyTableService autoKeyTableService;
@Autowired
private UUIDKeyTableService uuidKeyTableService;
@Autowired
private RandomKeyTableService randomKeyTableService;
@Test
void testDBTime() {
StopWatch stopwatch = new StopWatch("执行sql时间消耗");
// auto_increment key task
final String insertSql = "INSERT INTO user_key_auto(user_id,user_name,sex,address,city,email,state) VALUES(?,?,?,?,?,?,?)";
List<UserKeyAuto> insertData = autoKeyTableService.getInsertData();
stopwatch.start("自动生成key表任务开始");
long start1 = System.currentTimeMillis();
if (CollectionUtil.isNotEmpty(insertData)) {
boolean insertResult = jdbcTemplateService.insert(insertSql, insertData, false);
System.out.println(insertResult);
}
long end1 = System.currentTimeMillis();
System.out.println("auto key消耗的时间:" + (end1 - start1));
stopwatch.stop();
// UUID key task
final String insertSql2 = "INSERT INTO user_uuid(id,user_id,user_name,sex,address,city,email,state) VALUES(?,?,?,?,?,?,?,?)";
List<UserKeyUUID> insertData2 = uuidKeyTableService.getInsertData();
stopwatch.start("UUID的key表任务开始");
long begin = System.currentTimeMillis();
if (CollectionUtil.isNotEmpty(insertData)) {
boolean insertResult = jdbcTemplateService.insert(insertSql2, insertData2, true);
System.out.println(insertResult);
}
long over = System.currentTimeMillis();
System.out.println("UUID key消耗的时间:" + (over - begin));
stopwatch.stop();
// Random long key task
final String insertSql3 = "INSERT INTO user_random_key(id,user_id,user_name,sex,address,city,email,state) VALUES(?,?,?,?,?,?,?,?)";
List<UserKeyRandom> insertData3 = randomKeyTableService.getInsertData();
stopwatch.start("随机的long值key表任务开始");
Long start = System.currentTimeMillis();
if (CollectionUtil.isNotEmpty(insertData)) {
boolean insertResult = jdbcTemplateService.insert(insertSql3, insertData3, true);
System.out.println(insertResult);
}
Long end = System.currentTimeMillis();
System.out.println("随机key任务消耗时间:" + (end - start));
stopwatch.stop();
String result = stopwatch.prettyPrint();
System.out.println(result);
}
}The benchmark results show that auto_increment inserts are fastest, followed by random snowflake IDs, while UUID inserts are the slowest, especially as the table size grows to millions of rows.
Index Structure Analysis : Auto‑increment keys produce sequential, ordered InnoDB pages, minimizing page splits, random I/O, and fragmentation. UUIDs, being random, cause frequent page splits, random disk reads, and higher fragmentation, leading to degraded performance.
Despite its advantages, auto_increment has drawbacks: it reveals business growth patterns, can become a contention point under high concurrency, and incurs lock overhead.
Overall, the article concludes that for most MySQL workloads, the official recommendation to use auto_increment primary keys holds, while UUIDs and random keys should be used only when their specific benefits outweigh the performance costs.
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