![]() The emp_depto_idx index, that is like emp_pk, a B-tree with pointers to the heap, except that it does not enforce uniqueness.The emp_pk index (which is also the primary key), stored as a B-tree index where each element has a pointer to the employee's heap, with the exact page/offset in disk.The employees heap, which is basically the table stored sequentially (just like you imagine a table).On PostgreSQL there will be 3 structures: I'll use this table as reference (the code should be slightly modified to run on both RDBMS): CREATE TABLE employees (ĬREATE INDEX emp_depto_idx ON employees (depto_no) To avoid flame war, I'll just glance the way each storage work on querying, not really a benchmark. Internet says that Postgres is better for complex queries and subquering, but I still don't understand WHY is it better? Why InnoDB sequential scans are slower?.Why lookup through two indexes (InnoDB, lookup through non-PK index) is much slower? Does it requires two times more I/O or CPU? Can it compensate that huge benefit of PK lookup boost?.I understand why PK lookup is much better for MySQL. Which kind of queries are much faster with Postgres than with MySQL InnoDB? At the same time, an index scan requires traversing two indexes instead of one ( index -> PK index -> table row), meaning use of any index other than the primary key ends up being slower and sequential scans are slower still. less random disk I/O is required for PK lookup. With InnoDB, the table is a b-tree index ( clustered, physically sorted). This means a number of pieces of random disk I/O. a primary key lookup for a ( Postgres) table requires hitting the index, lookup up the location in the file then hit the heap table and pull the record. PostgreSQL tables are heap tables ( means no clustered index). ![]() ![]() Here is a brief retelling of the article: I've read Performance difference between MySQL and PostgreSQL for the same schema/queries.
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