Data blog — MySQL RSS



Table partitioning in relational databases

I would like to write shortly about table partitioning in relational databases. Table partitioning is basically dividing your data in a table into horizontal chunks, that can be (depending on the DB technology you use) indexed separately and stored on different disks. This allows you to address certain performance issues, if a table is large, and there are many inserts into it, and there is a requirement of providing reports on the data in this table. That table might be for example a transaction registry from your retail network. Partitioning allows separate 'read only' partitions from the active partitions. For example if you insert a lot of transactions to your registry table, they usually have a timestamp associated with them. You...

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Installing Docker for Windows

The post covers installation process of the Docker for Windows client, a utility that allows to run and manage docker images on the local machine. Docker images can be used to facilitate component and regression testing and are very important tool in the hands of a developer.

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Ranking of database engines

So it is January again and it is time for various trend reports and market share. Portal db-engines.com publishes, among other interesting content, periodic reports showing popularity of DBMS engines on the market. There is a number of factors taken into account, best described here. It is important to know that the report does not show the relative share of particular DBMS on the market, but rather its popularity among developers really.   What is striking though, that there are three leading technologies in terms of popularity - Oracle, MySQL and SQL Server. They are quite close to each other and quite apart from the fourth one - PostgreSQL. When you look at the historical trends chart, you can see that...

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NoSQL or SQL?

The article focuses on these two database technologies, but in fact it can be extended to the whole realms of RDBMS and NoSQL databases. Certain aspects of both domains can be considered as advantages or disadvantages, depending on the point of view and particular business case. The flexibility of schema in MongoDB is appealing to teams who implement applications dealing with unstructured data. The strictness of schema definition required by relational databases can be beneficial when the application needs to ensure that the data quality meets certain requirements.

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