A table cannot contain more than 1000 columns.

The InnoDB internal maximum key length is 3500 bytes, but MySQL itself restricts this to 3072 bytes.

Index key prefixes can be up to 767 bytes. See Section 12.1.13, “CREATE INDEX Syntax”.

The maximum row length, except for variable-length columns (VARBINARY, VARCHAR, BLOB and TEXT), is slightly less than half of a database page. That is, the maximum row length is about 8000 bytes. LONGBLOB and LONGTEXT columns must be less than 4GB, and the total row length, including BLOB and TEXT columns, must be less than 4GB.

If a row is less than half a page long, all of it is stored locally within the page. If it exceeds half a page, variable-length columns are chosen for external off-page storage until the row fits within half a page, as described in Section 13.6.11.2, “File Space Management”.

Although InnoDB supports row sizes larger than 65535 internally, you cannot define a row containing VARBINARY or VARCHAR columns with a combined size larger than 65535:

mysql> CREATE TABLE t (a VARCHAR(8000), b VARCHAR(10000),
    -> c VARCHAR(10000), d VARCHAR(10000), e VARCHAR(10000),
    -> f VARCHAR(10000), g VARCHAR(10000)) ENGINE=InnoDB;
ERROR 1118 (42000): Row size too large. The maximum row size for the
used table type, not counting BLOBs, is 65535. You have to change some
columns to TEXT or BLOBs

On some older operating systems, files must be less than 2GB. This is not a limitation of InnoDB itself, but if you require a large tablespace, you will need to configure it using several smaller data files rather than one or a file large data files.

The combined size of the InnoDB log files must be less than 4GB.

The minimum tablespace size is 10MB. The maximum tablespace size is four billion database pages (64TB). This is also the maximum size for a table.

InnoDB tables do not support FULLTEXT indexes.

InnoDB tables support spatial data types, but not indexes on them.

ANALYZE TABLE determines index cardinality (as displayed in the Cardinality column of SHOW INDEX output) by doing eight random dives to each of the index trees and updating index cardinality estimates accordingly. Because these are only estimates, repeated runs of ANALYZE TABLE may produce different numbers. This makes ANALYZE TABLE fast on InnoDB tables but not 100% accurate because it does not take all rows into account.

For InnoDB Plugin, the number of random dives can be changed by modifying the innodb_stats_sample_pages system variable. For more information, see the InnoDB Plugin manual.

MySQL uses index cardinality estimates only in join optimization. If some join is not optimized in the right way, you can try using ANALYZE TABLE. In the few cases that ANALYZE TABLE does not produce values good enough for your particular tables, you can use FORCE INDEX with your queries to force the use of a particular index, or set the max_seeks_for_key system variable to ensure that MySQL prefers index lookups over table scans. See Section 5.1.4, “Server System Variables”, and Section B.5.6, “Optimizer-Related Issues”.

SHOW TABLE STATUS does not give accurate statistics on InnoDB tables, except for the physical size reserved by the table. The row count is only a rough estimate used in SQL optimization.

InnoDB does not keep an internal count of rows in a table. (In practice, this would be somewhat complicated due to multi-versioning.) To process a SELECT COUNT(*) FROM t statement, InnoDB must scan an index of the table, which takes some time if the index is not entirely in the buffer pool. If your table does not change often, using the MySQL query cache is a good solution. To get a fast count, you have to use a counter table you create yourself and let your application update it according to the inserts and deletes it does. SHOW TABLE STATUS also can be used if an approximate row count is sufficient. See Section 13.6.13.1, “InnoDB Performance Tuning Tips”.

On Windows, InnoDB always stores database and table names internally in lowercase. To move databases in a binary format from Unix to Windows or from Windows to Unix, you should create all databases and tables using lowercase names.

For an AUTO_INCREMENT column, you must always define an index for the table, and that index must contain just the AUTO_INCREMENT column. In MyISAM tables, the AUTO_INCREMENT column may be part of a multi-column index.

While initializing a previously specified AUTO_INCREMENT column on a table, InnoDB sets an exclusive lock on the end of the index associated with the AUTO_INCREMENT column. In accessing the auto-increment counter, InnoDB uses a specific table lock mode AUTO-INC where the lock lasts only to the end of the current SQL statement, not to the end of the entire transaction. Other clients cannot insert into the table while the AUTO-INC table lock is held; see Section 13.6.4.3, “AUTO_INCREMENT Handling in InnoDB”.

When you restart the MySQL server, InnoDB may reuse an old value that was generated for an AUTO_INCREMENT column but never stored (that is, a value that was generated during an old transaction that was rolled back).

When an AUTO_INCREMENT column runs out of values, InnoDB wraps a BIGINT to -9223372036854775808 and BIGINT UNSIGNED to 1. However, BIGINT values have 64 bits, so if you were to insert one million rows per second, it would still take nearly three hundred thousand years before BIGINT reached its upper bound. With all other integer type columns, a duplicate-key error results. This is similar to how MyISAM works, because it is mostly general MySQL behavior and not about any storage engine in particular.

DELETE FROM tbl_name does not regenerate the table but instead deletes all rows, one by one.

Under some conditions, TRUNCATE tbl_name for an InnoDB table is mapped to DELETE FROM tbl_name. See Section 12.2.10, “TRUNCATE TABLE Syntax”.

In MySQL 5.1, the MySQL LOCK TABLES operation acquires two locks on each table if innodb_table_locks = 1 (the default). In addition to a table lock on the MySQL layer, it also acquires an InnoDB table lock. Older versions of MySQL did not acquire InnoDB table locks; the old behavior can be selected by setting innodb_table_locks = 0. If no InnoDB table lock is acquired, LOCK TABLES completes even if some records of the tables are being locked by other transactions.

All InnoDB locks held by a transaction are released when the transaction is committed or aborted. Thus, it does not make much sense to invoke LOCK TABLES on InnoDB tables in autocommit = 1 mode, because the acquired InnoDB table locks would be released immediately.

Sometimes it would be useful to lock further tables in the course of a transaction. Unfortunately, LOCK TABLES in MySQL performs an implicit COMMIT and UNLOCK TABLES. An InnoDB variant of LOCK TABLES has been planned that can be executed in the middle of a transaction.

The LOAD TABLE FROM MASTER statement for setting up replication slave servers does not work for InnoDB tables. A workaround is to alter the table to MyISAM on the master, then do the load, and after that alter the master table back to InnoDB. Do not do this if the tables use InnoDB-specific features such as foreign keys.

The default database page size in InnoDB is 16KB. By recompiling the code, you can set it to values ranging from 8KB to 64KB. You must update the values of UNIV_PAGE_SIZE and UNIV_PAGE_SIZE_SHIFT in the univ.i source file.

Currently, cascaded foreign key actions to not activate triggers.

You cannot create a table with a column name that matches the name of an internal InnoDB column (including DB_ROW_ID, DB_TRX_ID, DB_ROLL_PTR, and DB_MIX_ID). In versions of MySQL before 5.1.10 this would cause a crash, since 5.1.10 the server will report error 1005 and refers to error –1 in the error message. This limitation applies only to use of the names in uppercase.

InnoDB has a limit of 1023 concurrent transactions that have created undo records by modifying data. Workarounds include keeping transactions as small and fast as possible, delaying changes until near the end of the transaction, and using stored routines to reduce client-server latency delays. Applications should commit transactions before doing time-consuming client-side operations.