Architecture and Data Blog

When accessing the database using stored procedures for basic Create, Read, Update and Delete (CRUD) functions, or when you want to write triggers that capture the before and after values in tables, or when you want to create Plain Old Java Objects (POJO’s) that match the database objects, writing these by hand takes a lot of effort and also since the requirements are changing in an agile projects at a frequent rate, there will be design changes to meet the requirement changes, so the triggers, CRUD stored procedures or Data Access Objects (DAO) are going to be out of data, instead of hand coding, its better to generate the code, using the metadata of the database

Traditionally the data-team is used to sitting in their own area and working for many project teams by handling requests either via a ticketing system or vi email. The hand-over of work or throwing of work over the wall creates knowledge silos and inefficiencies.

Search engines have been great to find information on the internet with their ease of use and the ability to find cross linked content with specific keywords. This ease of use is being exploited by scammers and imposters.

On a recent project we had to connect to AWS Aurora postgres 10.6 version of the database in SSL mode using JDBC and Java 11 JRE. When the Aurora cluster is setup, we can force all connections to use SSL by using the options group settings (forceSSL=true), establishing secure connection from the application to the database is not as easy as it looks.

In all new development and sometimes during legacy codebase modernization, developers tend to add code quality checks and static analysis of codebase such as style checks, bug finders, cyclomatic complexity checking etc. into the CI/CD pipeline. When we inherit a codebase that has much PL/SQL and there is a desire to put the PL/SQL code base through the same types of code analysis, what options does a developer/dba have?

In this blog post, I will discuss ID generation techniques using the Object Relation Mapping frameworks such as Hibernate, Toplink, ActiveRecord, Entity Framework. When using hibernate or any other ORM mapping framework. There is a need to generate primary key values for the “id” columns. These values can be generated by using IDENTITY, SEQUENCE or TABLE strategies. Generating custom values for primary keys or other values is a topic for another blog post.

Many projects need addition of identical columns to all the tables created by the project. Audit columns are an example of such a requirement. The requirement is to add columns such as created_by, created_date, modified_by and modified_date to all the tables, these columns store, who created the row, when the row was created, who modified the row last and when was it modified. created_by and created_date are required to be present when the row is inserted and thus are required to be not nullable. Adding these columns to each and every table is a lot of work for developers.