Every online store has some central database that serves it: information about users, purchase data and other valuable data is stored there. As we said above, this is usually a relational database like PostgreSQL. Often the same database is used for various analytical tasks. For example, to analyze buyers’ behavior or to predict the demand for certain goods.
It turns out that the site database is used for storing data, for analytics, and for keeping the results of this analytics. And as the online store grows, the analytical load begins to affect the primary services: the site loads more slowly, slow down, or even crashes.
To reduce the site’s main database load and increase its stability. It is better to move the analytics to a separate analytical database. All data from the central database is transferred to it. And already, their analytical queries are formed, reports are built, and dashboards are displayed.
You can build such a system yourself: raise a separate database, set up integration with the central database, develop analytics tools. Or you can take a ready-made analytical DBMS or a comprehensive solution for big data analytics in the cloud.
For example, analytical databases such as Arenadata is one best example.
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