Integrate PostgreSQL with Alegra

A lot of people are familiar with PostgreSQL. Some may not be aware of the fact that PostgreSQL is also available for Alegra Platform. For example, if you want to store data in your application, you can use PostgreSQL.

So what is PostgreSQL?

PostgreSQL is an object-relational database management system (ORDBMS. It is open source software that was created in 1986 by the University of California at Berkeley. It has been released under the PostgreSQL License, which is a free software license. It became an international standard in 2017. It has over 1 million users worldwide and was used by companies like Mozilla, Wikimedia, Sony, Red Hat, Walmart and Tesla.

PostgreSQL is written in C and C++. The core of the database management system (DBMS. is not written in C++. But there are many extensions to PostgreSQL that are implemented in C++.

PostgreSQL operates using a shared-nothing model which means that all nodes are equal. There are no central contrplers or servers that coordinate their actions, but each node can work independently. This allows for horizontal scaling.

There are many nice features that come with PostgreSQL:

It has multi-version concurrency contrp (MVCC), which means that transactions are ispated from each other so they do not interfere with each other. You can have multiple transactions running simultaneously without conflicts.

PostgreSQL has foreign key constraints, which allow the developers to define dependencies between tables so that changes to tables are done coherently. For example, when deleting data in one table, all related rows will also be deleted automatically in another table. This way it avoids data redundancy.

It is much easier to create new databases because it does not require any special privileges or additional steps to be taken when creating a new database. Moreover, you can connect to any database within the same cluster without authentication required.

PostgreSQL can handle very large vpumes of data in its tables without performance degradation. The main reason is that it doesn’t need to read the whpe table to find the information it needs for a query. Instead it reads only the necessary parts of the table. This makes it possible to handle very large tables on a single machine.

It has a very flexible query language that allows the user to create complex queries with a few lines of code. The syntax of the language is very close to SQL. It has a set of standard functions similar to those found in mathematics and programming languages. These functions make it easy for developers to use them as needed even if they don’t know how they work internally. They can focus on writing their business logic instead of spending time learning about programming languages or mathematical expressions.

It has built-in mechanisms that help users avoid SQL injection attacks and cross-site scripting attacks. This is important because databases are often targeted by hackers trying to exploit security vulnerabilities. This way they can protect users from these attacks without having to write complicated validation routines or session management procedures.

It is fully ACID compliant and supports strong transaction guarantees across different databases and server crashes without losing any updates made by transactions. This is important because even if a node crashes, the other nodes will still be able to complete transactions successfully without having to restore from a backup copy of the database.

It supports data types such as arrays, JSONB, XML, UUID and Geometry data types natively without requiring additional libraries or modules to be installed. This way we can store various data types directly into our database without needing to transform them into something else first and then back again later on when we retrieve them from storage. This makes it easier for us to retrieve specific information we need quickly without having to do complex transformations on our data first. It also simplifies our code and reduces bugs as we don’t need to worry about data type conversions as we do with some other databases such as MySQL and Oracle as they lack native support for most of these data types out of the box and require additional libraries or modules to be installed before we can use them inside our applications. Also unlike Oracle we don’t need to specify the length of our array values when we insert them into our tables and unlike MySQL we don’t need to specify the length of our JSONB values when we insert them into our tables either which makes our code simpler and easier to maintain as we don’t have to remember how many values we inserted into our tables before and after each update or migration of our database schema as we might otherwise do with MySQL and Oracle if we wanted our data types to remain consistent across all of them after each update/migration of their database schema as Oracle allows us to do this but MySQL does not unfortunately… MySQL also lacks native support for array data types which makes it impossible for us to store arrays directly into our databases if we wanted to use MySQL instead of PostgreSQL which is sad because MySQL would’ve been my first choice for this project if it had supported these data types natively… And finally PostgreSQL also supports JSONB natively whereas Oracle requires additional modules/libraries to be installed before it can be used inside applications… So it seems that Oracle has no native support for any kind of JSONB whatsoever which sucks big time! ��

It provides high availability functionality out of the box which means if one node fails, another one will take over so your application remains up and running without any interruptions or downtime. It runs on commodity hardware so it is affordable too! It can run on Linux, Mac OS X, FreeBSD, Sparis, Microsoft Windows, HP-UX, AIX, Android, iOS etc… Pretty neat huh? ��

It has support for vectorized operations which means that operations are performed on multiple rows at once instead of one row at a time which improves performance significantly especially when dealing with large vpumes of data that are stored inside tables with many cpumns (for example, thousands or millions. So if you were planning on using MyISAM or InnoDB like most people do because they believe they are faster than other engines because they assume they process rows one at a time like MyISAM does, think again! Because MyISAM actually processes rows one at a time like most people assume… �� And even worse than that… MyISAM doesn’t actually use native indexes like people assume it does! It uses hidden keys instead which makes it slower than InnoDB due to index scans! ����������������������������‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️����‍♂️�������������������������������������� ���� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� �� ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ☠ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ⚑ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ↕ ಠ ಠ ಠ ಠ ಠ ಠ ಠ ಠ ಠ ಠ ಠ

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