In what is probably a surprise to many developers, MySQL currently stores its critical system tables in MyISAM instead of InnoDB. Since MyISAM isn’t ACID compliant, there is a chance for data loss or corruption when modifying system objects such as privilege. Morgan Tocker has announced thatthe MySQL team intends to use InnoDB for system tables.
MyISAMis the original storage engine for MySQL. It is based on IBM’s mainframe database technology known as Indexed Sequential Access Method orISAM. Because it doesn’t support transactions and the associated overhead, MyISAM tends to be faster than other database storage engines. The downside of this is that it isn’t ACID compliant and is prone to data corruption, especially during power failure scenarios.
The primary alternative to MyIASM isInnoDB, which was created by the Innobase Oy. Because it offers ACID-compliant transactions and foreign key constraints, among other features, Oracle made it the default storage engine in MySQL 5.5.
Other storage engines for MySQLstill in active development include:
- Archive by Oracle
- Aria by Monty Program
- CONNECT by Monty Program
- CSV by Oracle
- NDB by Oracle
- InfiniDB by Calpont
- TokuDB by TokuTek
- XtraDB by Percona GPL
- FederatedX by Monty Program
- CassandraSE by Monty Program
- sequence by Monty Program
- mroonga by Monty Program
While MySQL is planning to support InnoDB only, the forkMariaDBhas instead chosen to be fully agnostic.
As far as release dates are concerned, Morgan writes,
The DMR 'release train' model requires for features to be stable before being merged, rather than releases holding for specific features. So I don't want to get ahead of myself here for work that is in early development. Soon :D

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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