The following table compares the features of PostgreSQL vs. The world’s most advanced open source database. Multiple storage engines e.g., InnoDB and MyISAM The world’s most popular open source database. No TEMP or TEMPORARY keyword in DROP TABLE statement Support the TEMP or TEMPORARY keyword in the DROP TABLE statement that allows you to remove the temporary table only. Support CASCADE option to drop table’s dependent objects e.g., tables and views. PostgreSQL TRUNCATE TABLE supports more features like CASCADE, RESTART IDENTITY, CONTINUE IDENTITY, transaction-safe, etc. MySQL TRUNCATE TABLE does not support CASCADE and transaction safe i.e. once data is deleted, it cannot be rolled back. Programming languages for stored procedures Yes (Supported since MySQL 8.0.16, Before that MySQL just ignored the CHECK constraint) Must be a constant or CURRENT_TIMESTAMP for TIMESTAMP or DATETIME columns Support many advanced types such as array, hstore, and user-defined type. ![]() Ruby, Perl, Python, TCL, PL/pgSQL, SQL, JavaScript, etc. MySQL supports covering indexes that allow data to be retrieved by scanning the index alone without touching the table data. This is advantageous in case of large tables with millions of rows. Support triggers that can fire on most types of command, except for ones affecting the database globally e.g., roles and tablespaces.Of those four, only PostgreSQL and MySQL are open-source databases. Being open-source means these two are completely free, which also has a significant (positive!) impact on database popularity. The possibility that anyone can modify the software leads to flexibility and a community providing quality support. It’s only multiplied by the popularity of the two databases and the sheer number of its users and contributors.Īll this means both PostgreSQL and MySQL dialects are almost unavoidable in the data science world.īut how do you decide which one you should use? Nobody has ever decided between two choices based on their similarities. The differences are what make, well, the difference. As a data scientist, you’re probably not that concerned about database architecture, performance, integrity, and all other stuff RDBMS is for. What will make you give a pass (or not) to a certain database are the possibilities of the SQL dialect and how well it serves you to do your job. That’s why we’re going to look into the syntax differences between PostgreSQL and MySQL and their possibilities. Here’s the overview of the differences we’ll cover, with detailed explanations following. There’s nothing because your string in the WHERE clause doesn’t match the case of data in the column program_status. PostgreSQL is also case-sensitive when it comes to column and table names. ![]() ![]() If the above table was named Los_Angeles_restaurant_health_inspections and the columns are Serial_Number and Program_Status, your PostgreSQL code should be: SELECT “Serial_Number”,įROM Los_Angeles_restaurant_health_inspections Or, to be more specific, case-sensitivity becomes important if your column and/or table name includes upper case. ![]() Names with the uppercase should be double-quoted and match the table or column case. When the names are all in lowercase, and you write your query in uppercase, this query would still work: SELECT SERIAL_NUMBER,įROM LOS_ANGELES_RESTAURANT_HEALTH_INSPECTIONS Some workarounds to make PostgreSQL case-insensitive include using citext extension, ILIKE operator, or LOWER() function. Learning any of these two SQL dialects is a wise decision.
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