![]() Support CASCADE option to drop table’s dependent objects e.g., tables and views. Support the TEMP or TEMPORARY keyword in the DROP TABLE statement that allows you to remove the temporary table only. No TEMP or TEMPORARY keyword in DROP TABLE statement Multiple storage engines e.g., InnoDB and MyISAM The world’s most popular open source database. The world’s most advanced open source database. The following table compares the features of PostgreSQL vs. ![]() ![]() MySQL has been famous for its ease of use and speed, while PostgreSQL has many more advanced features, which is the reason that PostgreSQL is often described as an open-source version of Oracle. Both PostgreSQL and MySQL are time-proven solutions that can compete with enterprise solutions such as Oracle and SQL Server. MySQL is an important decision when it comes to choosing an open-source relational database management system. In contrast, Postgres with a spatial index is fast for any number of points.PostgreSQL vs. I have seen acceptable interactive performance for 100k points, with performance dropping off after that. On the other hand, it can do bounding box comparisons to eliminate many geometries quite quickly. If you pick an engine that does not support spatial indexes, MySQL is forced to do a full table scan, which takes O(N) time. It really depends on how many businesses you're searching for. Postgres is also a quite mature and widely used relational database these days. If you use Postgres, you can have both referential integrity and fast spatial lookups. So if you pick MySQL, you need to choose between referential integrity and fast spatial lookups. ![]() Note that foriegn key constraints are not compatible with MyISAM, which is the only MySQL database engine which supports spatial indexes. (MySQL is a well tested database for years and most of my data is relational, so I was planning to use MySQL or Microsoft SQL Server) Almost every time MySQL is mentioned on that page, it is to describe a feature that it does not support, but that Postgres does. However, there is a long list of features which Postgres supports and MySQL doesn't. It's not that MySQL doesn't support spatial data. The reason why they suggest using Postgres is that it has better support for spatial data. Would there be any processing disadvantages in context to algorithms used to compute nearby businesses if I choose to go with MySQL, how would it make my system slow? ( MySQL is a well tested database for years and most of my data is relational, so I was planning to use MySQL or Microsoft SQL Server) I was wondering what are the specific advantages of using PostgreSQL over MySQL in context to computing and fetching the location related fields. Customers can find nearby businesses around him.Both customer and business will have their locations stored.This is not how database is, only for rough idea or project.Here a user can register as a customer as well as a business ( customer's and business's name/address etc (all) fields will be separate, even if its the same user) There are multiple Tutorials/Questions over the Internet/Youtube/StackOverflow for finding nearyby businesses, given a location, for example ( Question on StackOverflow) :īut one thing common in these all is that they all prefers PostgreSQL (instead of MySQL) for Django's Geodjango library
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