Architecture and Data Blog

Lots of time hand coded SQL is written in the applications for performance sake, getting data using complex SQL out of the tables. As the database structure changes it becomes really hard to find out all the SQL that needs to be changed. In other cases SQL is generated based on certain conditions in the code and its hard to find if the generated SQL is valid after database changes are done.

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.