In relational databases, database metadata, such as information about the MySQL server, the name of a database or table, the data type of a column, or access privileges are stored in the data dictionary and/or system catalog. MySQL's provides database metadata in a special schema called INFORMATION_SCHEMA. There is one INFORMATION_SCHEMA within each MySQL instance. It contains several read-only tables that you can query to obtain the information that you are looking for. In today's blog, we'll explore a few practical uses for the INFORMATION_SCHEMA, as demonstrated using Navicat Premium.
If you work regularly with MySQL or MariaDB, then you will probably find Navicat Premium or Navicat for MySQL to be indispensable. In addition to MySQL and MariaDB, Navicat for MySQL also supports a number of cloud services, including Amazon RDS, Amazon Aurora, Oracle Cloud, Google Cloud, Microsoft Azure, Alibaba Cloud, Tencent Cloud and Huawei Cloud. Navicat Premium is a database development tool that allows you to simultaneously connect to MySQL, MariaDB, MongoDB, SQL Server, Oracle, PostgreSQL, and SQLite databases from a single application, and is also compatible with cloud databases. Both help you create views, queries and functions using an easy-to-use GUI interface. Moreover, you can save your work to the Cloud for reuse and collaborating with team members.
In today's blog, I'll be sharing a few tips and tricks for MySQL that you can apply using either Navicat for MySQL or Navicat Premium.
A database view is a virtual or logical table which is comprised of a SELECT query. Much like a database table, a view also consists of rows and columns that you can query against. Most database management systems, including MySQL, even allow you to update data in the underlying tables through the view, but with some caveats. In today's blog, we'll learn what a view is and how to create one for MySQL 8 using Navicat Premium as our client.
Most relational databases - including MySQL, MariaDB, and SQL Server - support stored procedures and functions. Stored procedures and functions are actually very similar, and can in fact be utilized to accomplish the same task. That being said, there are some crucial differences between the two that need to be considered when deciding which to use for a given job. We'll go over these in today's blog
Regular expressions (regex) provide a way to match strings against a pattern so that your searches are "fuzzy" rather than exact. MongoDB comes with a regex engine built in so you can dig up documents even if you don't know exactly what the exact Field value is that you're looking for. In today's blog we'll learn how to use regexes in MongoDB, using Navicat for MongoDB.
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