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What is ClickHouse?
ClickHouse is an open-source column-oriented DBMS (or database management system) primarily used for OLAP (or the Online Analytical Processing of queries). It is capable of blazing fast generation of real-time analytical data and reporting utilizing SQL queries. It is fault tolerant, scalable, highly reliable and contains a feature rich tool set.
In a regular database, data is stored in tables, columns, and rows. In a table, the related values are physically stored side by side in one row, which is critical to how it operates. This is how most string type databases work.
Continue reading “How to Install and Configure ClickHouse on Ubuntu 20.04”
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MySQL via Command Line 101: Basic Database Interaction
In this article, we will be discussing how to use MySQL to create a new user on Linux via the command line. We will be working on a Liquid Web core-managed server running CentOS version 6.5 as the root user. The commands used should also work on later versions of MySQL on CentOS as well.
MySQL is a relational database management application primarily used on Linux and is a component of the LAMP stack (Linux, Apache, MySQL, and PHP).
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- Log in as the root user.
- Have access to a terminal.
- Basic knowledge of the command line.
Reading Time: 6 minutes
Data in a MySQL/MariaDB database is stored in tables. A simple way of thinking about indexes is to imagine an extensive spreadsheet. This type of system is not always conducive to quick searching; that’s where an index becomes essential. If there is no index, then the database engine has to start at row one and browse through all the rows looking for the corresponding values. If this is a small table, then it is no big deal, but in larger tables and applications where there can be tables with millions and even billions of rows, it becomes problematic. As you can imagine, searching through those rows one by one will be time-consuming, even on the latest hardware. The solution is to create an INDEX (or more than one) for your data.
Continue reading “MySQL Performance: MySQL/MariaDB Indexes”