What Is InnoDB Storage Engine

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∟What Is InnoDB Storage Engine

This section describes the InnoDB storage engine, the default storage engine in the newer versions of MySQL server.

What InnoDB Storage Engine - InnoDB Storage Engine is a general-purpose storage engine that balances high reliability and high performance. InnoDB storage engine is the default storage engine in the newer versions of MySQL server.

Key advantages of InnoDB storage engine:

Its DML operations follow the ACID model, with transactions featuring commit, rollback, and crash-recovery capabilities to protect user data.
Row-level locking and Oracle-style consistent reads increase multi-user concurrency and performance.
InnoDB tables arrange your data on disk to optimize queries based on primary keys. Each InnoDB table has a primary key index called the clustered index that organizes the data to minimize I/O for primary key lookups.
To maintain data integrity, InnoDB supports FOREIGN KEY constraints. With foreign keys, inserts, updates, and deletes are checked to ensure they do not result in inconsistencies across related tables.

InnoDB storage engine has the following benefits:

If the server unexpectedly exits because of a hardware or software issue, regardless of what was happening in the database at the time, you don't need to do anything special after restarting the database. InnoDB crash recovery automatically finalizes changes that were committed before the time of the crash, and undoes changes that were in process but not committed, permitting you to restart and continue from where you left off.
The InnoDB storage engine maintains its own buffer pool that caches table and index data in main memory as data is accessed. Frequently used data is processed directly from memory. This cache applies to many types of information and speeds up processing. On dedicated database servers, up to 80% of physical memory is often assigned to the buffer pool.
If you split up related data into different tables, you can set up foreign keys that enforce referential integrity.
If data becomes corrupted on disk or in memory, a checksum mechanism alerts you to the bogus data before you use it. The innodb_checksum_algorithm variable defines the checksum algorithm used by InnoDB.
When you design a database with appropriate primary key columns for each table, operations involving those columns are automatically optimized. It is very fast to reference the primary key columns in WHERE clauses, ORDER BY clauses, GROUP BY clauses, and join operations.
Inserts, updates, and deletes are optimized by an automatic mechanism called change buffering. InnoDB not only allows concurrent read and write access to the same table, it caches changed data to streamline disk I/O.
Performance benefits are not limited to large tables with long-running queries. When the same rows are accessed over and over from a table, the Adaptive Hash Index takes over to make these lookups even faster, as if they came out of a hash table.
You can compress tables and associated indexes.
You can encrypt your data.
You can create and drop indexes and perform other DDL operations with much less impact on performance and availability.
Truncating a file-per-table tablespace is very fast and can free up disk space for the operating system to reuse rather than only InnoDB.
The storage layout for table data is more efficient for BLOB and long text fields, with the DYNAMIC row format.
You can monitor the internal workings of the storage engine by querying INFORMATION_SCHEMA tables.
You can monitor the performance details of the storage engine by querying Performance Schema tables.
You can mix InnoDB tables with tables from other MySQL storage engines, even within the same statement. For example, you can use a join operation to combine data from InnoDB and MEMORY tables in a single query.
InnoDB has been designed for CPU efficiency and maximum performance when processing large data volumes.
InnoDB tables can handle large quantities of data, even on operating systems where file size is limited to 2GB.

Best practices for InnoDB storage engine provided in MySQL reference manual:

Specify a primary key for every table using the most frequently queried column or columns, or an auto-increment value if there is no obvious primary key.
Use joins wherever data is pulled from multiple tables based on identical ID values from those tables. For fast join performance, define foreign keys on the join columns, and declare those columns with the same data type in each table. Adding foreign keys ensures that referenced columns are indexed, which can improve performance. Foreign keys also propagate deletes and updates to all affected tables, and prevent insertion of data in a child table if the corresponding IDs are not present in the parent table.
Turn off autocommit. Committing hundreds of times a second puts a cap on performance (limited by the write speed of your storage device).
Group sets of related DML operations into transactions by bracketing them with START TRANSACTION and COMMIT statements. While you don't want to commit too often, you also don't want to issue huge batches of INSERT, UPDATE, or DELETE statements that run for hours without committing.
Do not use LOCK TABLES statements. InnoDB can handle multiple sessions all reading and writing to the same table at once without sacrificing reliability or high performance. To get exclusive write access to a set of rows, use the SELECT ... FOR UPDATE syntax to lock just the rows you intend to update.
Enable the innodb_file_per_table variable or use general tablespaces to put the data and indexes for tables into separate files instead of the system tablespace. The innodb_file_per_table variable is enabled by default.
Evaluate whether your data and access patterns benefit from the InnoDB table or page compression features. You can compress InnoDB tables without sacrificing read/write capability.
Run the server with the --sql_mode=NO_ENGINE_SUBSTITUTION option to prevent tables from being created with storage engines that you do not want to use.