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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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Graph extensions in SQL Server 2017

We have been talking a bit about graph databases in recent posts. Data Modelling and Monty Python What are the advantages of using a graph database? The rise of the graph databases. Well, it turns out that also SQL Server jumps on the bandwagon and makes first steps towards graph processing.  In the first release, the functionality will be a bit limited, but you can write some workaround code for certain types of graph traversals. The functionality of the first release is explained in the FAQ article on the Technet blog.   There are advantages of the SQL Server solution. SQL Server has become an industry standard and one of the main players on the RDBMS market. The graph functionality...

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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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