Today, a relational database like MariaDB Server (part of MariaDB TX) can read, write and query both structured and semi-structured data, together. MariaDB Server supports semi-structured data via dynamic columns and JSON functions. This blog post will focus on JSON functions with MariaDB Server, using examples to highlight one of they key benefits: data integrity.
MariaDB announced BSL 1.0 together with MariaDB MaxScale 2.0 in August 2016. After having the license “in the wild” for a few months we’ve been reaching out to Open Source advocates to get feedback on the BSL.
This is a continuation of my previous blog, where we will focus on some more advanced features related to Dynamic Columns. For an introduction to Dynamic Columns please refer to my previous blog.
For certain situations, the static structure of tables in a relational database can be very limited. Each column is statically defined, has a pre-defined type and you can only enter a value of that type into the column.You can be creative and list multiple values in one column, but then those values are not generally easily accessed and manipulated with other functions. You have to use an API or contortions of a function like SUBSTRING() to pull out a value you want. Even then, you have to know what is contained in the column to be able to manipulate it properly.
Dynamic columns came to my attention a few days back. Since then I read a little bit more in the documentation (see Dynamic columns in the Knowledge Base) and played with it a little. The reason I became curious was that it brings the 'schema less' feature of the NoSQL world into the MySQL world. It was implemented in MariaDB v5.3, and MariaDB 10.0 introduces several enhancements.
In my previous blog post, I described some of the key new replication features in MariaDB 10 that let this powerful open-source database shine in web-scale and analytical applications.
In my previous role as the manager of an enterprise-grade public cloud, I’ve had the opportunity to work with many enterprises from across industries and across the world. All of these companies were looking for new ways to better understand and serve their customers, to improve efficiency, and improve their financials. There were many different approaches, but they all had one thing in common; it is all about data. Every day nearly 4 exabytes of data is created. This data holds great value for business, science and society.