What is a Database Query?

• Database Query Definition

  Database Query Definition

  In everyday language, a query is simply a request for information. Similarly, the meaning of a query in database management is a request for data. If you need to access, manipulate, delete, or retrieve data from your relational database, you’ll need a database query written using a specific syntax.

  Once you execute the query, your database engine will retrieve information from the database table (or a combination of tables) and transform it into a human-readable format like a table, graph, or pictorial. You can then examine the data from your database to gain insights into activities and trends.
• What is a query in a database?

  What is a query in a database?

  Essentially, queries enable DBAs and others to retrieve information from and take action on databases. Relational databases are organized collections of data, and without them and the information they contain, our applications wouldn’t be able to work as intended. So, having a secure and well-managed database is critical for an application’s success.

  However, relational database management systems (RDBMS) can be vast and contain an overwhelming amount of data. In an RDBMS, tables consist of rows and columns of data. Each of the table’s rows is for a specific entity, and the associated columns will define the entity’s attributes. For example, if you have a customer data table, every row will contain information about each of your customers. The columns will hold their information, such as name, address, and birthday. Now, imagine you have 30,000 customers, each with their own ID numbers, names, addresses, birthdays, and more. Database management can become extremely complicated and time-consuming. This is where database queries come in.

  Using database queries will filter data into a single table for more straightforward analysis. Database queries can also help quickly aggregate data and read, update, create, and delete items in your database. You can also use a database query to find or summarize specific information quickly. You can also use more advanced queries for counting, performing calculations, and automating various data management tasks like reviewing current data.

  If you want to reuse a query with different values or a different purpose, you’ll need to parameterize it. This means using placeholders for parameters instead of constant values. Then, when you execute the query, the placeholders will be replaced. Using query parameters can reduce the number of queries you’ll have to write. Still, not all queries can be fully parameterized.

  It’s also important to note queries often need to be tuned or optimized to improve overall database performance. This is because your database is limited by the hardware’s processing capabilities. Inefficient, slow queries or those with errors can drain resources. They can also result in slow performance, create bottlenecks, or cause a loss of service. To improve performance and reduce query execution time, you’ll need to optimize your queries or reduce the number of calculations required to retrieve information.

  On the other hand, optimizing every query can be a waste of time and energy, so you must be selective when deciding which ones to tune. To determine if a query needs to be optimized, look at its execution plan, duration, CPU time, and logical and physical reads. You can also compare these to historical data or established baselines.

  Common ways to optimize database query execution times include removing duplicate data, limiting your dataset via subqueries, simplifying joins, avoiding running queries in a loop, and adjusting syntax. For example, you might use ‘SELECT <fieldnames> FROM’ instead of ‘SELECT * FROM’ to retrieve specific information with SQL statements more quickly.
• What’s the most common database query language?

  What’s the most common database query language?

  DBAs rely on various database query languages to help optimize their systems and ensure the information stored within databases is accessible yet secure; however, Structured Query Language (SQL) is the most popular database query language.

  SQL is the standard database language for major RDBMSes, such as MySQL, Oracle, Microsoft Access, SQL Server, IBM Db2, and Postgres. It was developed by IBM in the 1970s alongside the Query By Example (QBE) system, which enabled users to input information into a graphical user interface and build queries to search or filter through relational or object-oriented databases based on that information.

  Scalable, robust, and compatible with the QBE system, it’s easy to see why SQL remains popular. With short code snippets, you can create, store, retrieve, read, and manipulate data in your database. However, it’s important to note some NoSQL databases don’t require SQL, such as Redis, Cassandra, MongoDB, and Risk.
• How to run a SQL query against a database

  How to run a SQL query against a database

  If you’re unfamiliar with database queries, running a SQL query on your database may seem daunting. However, it isn’t as complicated as you might think. Plus, once you know how to write and run SQL queries, your tasks will be much easier.

  To run a SQL query on your database, you’ll need:

  • A database engine: Database engines serve as data repositories. There are countless database engines available, including Oracle, MySQL, SQL Server, Db2, and PostgreSQL. Smaller organizations often opt for MySQL, PostgreSQL, or other free database engines, while larger companies generally use larger, robust ones. Once you choose your database engine, installation is relatively straightforward.
  • A SQL client: You’ll also need a SQL client to communicate with your chosen database engine. Some database engines will automatically install SQL clients, but others may require you to download, install, and configure a SQL client after installing the database engine.
  • A SQL query: Finally, you’ll need to craft and run a SQL query. SQL queries vary in complexity, allowing you to do everything from retrieving all results within a specific table to filtering for particular results and adding new data.

  To execute a query, you’ll need to learn the proper syntax. For example, you can write a delete query if you need to remove a customer from your database. You might write DELETE FROM Customers WHERE CustomerName=‘John Smith’ and execute your query. However, a few things will happen before the matching records are deleted from the table.

  First, the database engine will review the SQL statement to check the validity of your syntax. If there’s a typo or other error, the database engine’s parser will let you know, and you’ll need to modify your query.

  The parser will then examine the data dictionary to determine if the tables, functions, and views you have queried exist. It will also ensure you have permission to access them and see if you’ve recently executed this particular query. If so, it will check your cache of execution plans (also called explain plans by some engines). These plans contain a map and the order of operations needed to collect the data you’ve requested.

  If your database engine finds an existing plan, it will execute it. If not, it will generate several execution plans using statistics and metadata about your table’s data, choose the plan requiring the least CPU usage, and then gather the requested data.