As a database professional, I work with both databases on a regular basis, and I typically use all the features of both databases for design and implementation.
I have got many replies to write about the core differences between PostgreSQL and MySQL.

As innovation on these databases has progressed, each development community has actively made changes to address their respective sets of perceived disadvantages.
The result that it has gotten more difficult to objectively determine which database is likely to be better suited for a given application.

MySQL is controlled by Oracle, whereas Postgres is available under an open-source license from the PostgreSQL Global Development Group.

PostgreSQL is closer to the ANSI SQL standard, MySQL is closer to the ODBC standard.

One of the most notable differences between MySQL and PostgreSQL is the fact that you can’t do nested subqueries of subselects in MySQL. MySQL doesn’t support CTE, window functions, full outer joins and arrays.

Compare to PostgreSQL, MySQL has its own large user community and various type of materials.

MySQL uses nonstandard ‘#’ to begin a comment line and PostgreSQL use ‘–‘ to begin a comment line.

MySQL provides different type of table storage engines like: InnoDB, MyIsam, Memory. PostgreSQL does not provide different type of table stroage engines.

PostgreSQL is case-sensitive for string comparisons. The field “DbRnd” is not the same as the field “dbrnd”. This is a big change for many users from MySQL and other small database systems.

PostgreSQL has some nice features like: generate_series, custom aggregate functions, arrays etc. other hand MySQL has also some nice feature like: session variables in queries, FORCE INDEX, etc.

In PostgreSQL, when you are inside a transaction almost any operation can be undone. There are some irreversible operations (like creating or destroying a database or tablespace), but normal table modifications can be backed out by issuing a ROLLBACK via its Write-Ahead Log design.

MySQL doesn’t support any sort of rollback when using MyISAM. With InnoDB, the server has an implicit commit that occurs even if the normal auto-commit behavior is turned off. This means that any single table alteration or similar change is immediately committed.

Postgres obliterates MySQL in all manner of query-level goodness, and we can use Postgres for data mining and batch analytics databases, where we run lots of very large, hand-coded queries that can take advantage of Postgres’ advantages in join methods (MySQL only supports Nested Loop and Nested Loop over Index, while Postgres supports numerous methods), generally richer querying capabilities, and other good stuff like partial indexes can be used extensively.

PostgreSQL uses a robust locking model called MVCC that limits situations where individual clients interfere with each other. A short summary of the main benefit of MVCC would be “readers are never blocked by writers”.

MySQL’s InnoDB implements MVCC using a rollback segment and InnoDB databases supports all four SQL standard transaction isolation levels.

PostgreSQL uses cost-based query optimization methods in order to get good performance for many different types of joins. Query costs are assessed based on planner statistics collected when tables are analyzed combined with adjustable planner costs and advanced features such as the Genetic Query Optimizer.

MySQL doesn’t have this level of sophistication in its planner, and the tunables for Controlling Query Optimizer Performance are crude. Developers instead do things like explicitly provide index hints to make sure joins are executed correctly.

PostgreSQL has different replication options than MySQL. MySQL has no point-in-time recovery.

One operation that PostgreSQL is known to be slow performing is doing a full count of rows in a table, typically using this SQL:

SELECT COUNT(*) FROM your_table_name;

The reason why this is slow is related to the MVCC implementation in PostgreSQL. The fact that multiple transactions can see different states of the data means that there can be no straightforward way for “COUNT(*)” to summarize data across the whole table; PostgreSQL must walk through all rows, in some sense.

In MySQL, MyISAM tables cache the row count information, making this type of count operation almost instant. But if you’re using InnoDB instead, this is no longer the case and on InnoDB can’t assume that a full row count will be fast.

This is one of the very important post for all PostgreSQL Database Professionals.

In this post, I am sharing a small, but very powerful script to know about the Live Tuples (Rows) and Dead Tuples (Rows) of the PostgreSQL Object like: Tables and Indexes.

If you don’t know about the MVCC (Multi Version Concurrency Control), Please visit this article.

What is Multi Version Concurrency Control (MVCC)

PostgreSQL is based on MVCC Architecture.

In MVCC Architecture, When you update or delete any row, Internally It creates the new row and mark old row as unused.

This kind of data, we call as Dead Tuples or Dead Rows. (We can also say like, This is an internal fragmentation).

Periodically, We should find dead rows of the object and we should remove it using VACUUM techniques of PostgreSQL.
By this way, we can increase the overall performance of PostgreSQL Database Server.

PostgreSQL: Short note on VACUUM, VACUUM FULL and ANALYZE

Find out Live Tuples or Dead Tuples using two different scripts.

Using system function and pg_class:

SELECT 
	relname AS ObjectName
	,pg_stat_get_live_tuples(c.oid) AS LiveTuples
	,pg_stat_get_dead_tuples(c.oid) AS DeadTuples
FROM pg_class c;

Using pg_stat_user_tables:

SELECT 
	relname AS TableName
	,n_live_tup AS LiveTuples
	,n_dead_tup AS DeadTuples
FROM pg_stat_user_tables;