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.
Many a times ER models are created by the data team and are not shared outside of the data team generally for the lack of tools licenses, since its not feasible for the entire team to purchase licenses for the ER modelling tools such as Erwin Data Modeller or Er Studio
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?
Loading data into tables is needed many times on projects to load test, Liquibase provides a method to load data into tables with lots of customization. In the example shown below, I’m loading zip code data with the following column layout
"Zipcode","ZipCodeType","City","State","LocationType","Lat","Long","Location","Decommisioned","TaxReturnsFiled","EstimatedPopulation","TotalWages"
In many development shops, developers are not allowed to access the database schema directly, and are not allowed to create tables, indexes, views etc, instead are given access via a different schema that allows SELECT, UPDATE and DELETE access on data. The general reason is to avoid developers creating database objects without
IN many projects, there are tables which need default audit columns such as Created_By, Created_Date, Modified_By, Modified_date and other columns that need to be updated every time some actions are done against the tables and/or columns. This type of functionality can be implemented using triggers.
In relational database usage the pattern of migrations is well understood and has gained widespread acceptance. Frameworks such as DBDeploy, DBMaintain, MyBatis migrations, Flyway, Liquibase, Active Record Migrations and many others. These tools allow to migrate the database and maintain the version history of the database in the database.
While doing evalauation of NoSQL databases, we had a 10 node riak cluster and wanted check how a similar setup would work with mongodb. So started to setup a 10 node mongodb cluster. Since this was for initial spikes, we decided to set this up on a single machine as with the other test setup using Riak.
When trying to evaluate NoSQL databases, its usually better to try them out. While trying them out, its better to use them with multiple node configurations instead of running single node. Such as clusters in Riak or Replica-set in mongodb maybe even a sharded setup. On our project we evaluated a 10 node Riak cluster so that we could experiment with N, R and W values and decide which values where optimal for us. In Riak here is what N, R and W mean.