MySQL
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Parsing and SQL Data Types: A Complete Guide

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This blog will walk you through everything you need to know about SQL data types when parsing data. Have a read!

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Dbvisualizer DBVISUALIZER
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Parsing data is of interest to many developers, data analysts, and DBAs alike as parsing allows us to turn data sets into formats we desire. Contrary to a popular belief, one of the key elements of parsing are SQL data types.

Data types in SQL are a core element of data parsing because:

  1. Parsed data often involves strings, numeric, and other values.
  2. The length of the data types is often a direct limiter in terms of how long your string(s) in a specific column can be.
  3. The data types available to you vary based on what database management system you find yourself using.

Let’s dive into the world of SQL data types!

SQL Data Parsing Explained

Parsing, in simple words, is turning data formatted in one way into data formatted in another way. For example, if you have a table with columns id, username, email, registration_time, and hashed_password and only extract username and email columns from that data set, that data set is parsed. However, this is not the only example of data parsing.

Say you have a date value like 2025-08-01. Once this date is inserted into any column, your database will parse this value according to its internal rules. If your column has a data type of date, our database will first convert the string into an internal date representation (e.g. a numeric timestamp, a date object, etc.), then store the value as the object. That’s why you may insert a value of 2025-08-01, but see August 1st, 2025 instead. Find out more in our guide on SQL data types.

Parsing and data types have a lot in common, too.

SQL Data Types Explained

SQL data types can and do vary based on what database management system you find yourself using.

For exmaple, data types available in newer versions of MySQL (MySQL ≥8.0) include the following:

Numeric data types

  • TINYINT takes up 1 byte a character
  • SMALLINT takes up 2 bytes a character
  • MEDIUMINT takes up 3 bytes a character
  • INT/ INTEGER takes up 4 bytes a character
  • Various other data types that take a variety of bytes per character. Check the documentation for more details

String data types

  • CHAR(n) for fixed-length data
  • VARCHAR(n) for variable-character data
  • TEXT for data up to 65,535 bytes
  • TINYTEXT for data up to 255 bytes
  • MEDIUMTEXT for data up to ~17M bytes
  • LONGTEXT for data up to ~4 billion bytes

Date and time data types

  • DATE for dates in the YYYY-MM-DD format
  • DATETIME for dates formatted like YYYY-MM-DD HH:MM:SS
  • TIMESTAMP for timestamps with time zones
  • TIME for strings like HH:MM:SS
  • YEAR for storing four-digit year values.

Binary data types

  • BLOB (binary large object, max 64kB of storage)
  • TINYBLOB (max 255 bytes of storage)
  • MEDIUMBLOB (max 16MB of storage)
  • LONGBLOB (max 4GB of storage)

Additional data types starting from MySQL 8.0

  • ENUM depicts an enumerated list of values
  • SET depicts a set of string values

These are some of the data types available in MySQL. However, the specific SQL data types available for use for you will depend on your specific use case.

SQL Data Types and Your Use Case

Indeed, your use case has a lot to do with what SQL data types you find yourself using. Let’s explore a couple:

a. You’re running a data breach search engine and are parsing data in data breaches:

  1. You would import the data breach into your database management system of choice. The data breach would likely include usernames, email addresses, registration dates, and other information.
  2. The data types you would find yourself initially using would likely be of medium-length VARCHAR values (keep in mind that the summed up value of VARCHAR character length cannot exceed 65,535 meaning that you cannot have more than 257 columns with a maximum length of 255.)
  3. After your data is inserted, you would run SQL queries to drop everything except the username and email columns.
  4. After only the username and email columns remain, you would add additional columns to match the structure of the rest of the data breaches you have in store.

b. Your use case involves storing password hashes:

  1. You would import the data in question into your database management system.
  2. You would extract the password hashes from the data.
  3. Depending on what kinds of password hashes you find yourself storing, you would likely use CHAR(32|64) or VARCHAR(32-128) SQL data types to store them.

c. You need to record user age or other small numbers and the registration dates from a bigger set of data:

  1. You would import the data in question into your database management system.
  2. You would extract the column with the user age or other necessary data.
  3. You would extract the user age or other small numbers into a column with a TINYINT or SMALLINT data type.
  4. You would extract the registration dates of people into a column having a DATE data type.

As you can see, parsing data in SQL almost always involves specific data types and changing them up as you see fit.

Managing data types and other things when parsing data can get quite complex, though, and to eliminate that complexity, you need to turn to SQL clients like DbVisualizer. This tool comes with a free 21-day trial so that you can try out all of the features of the database client and see if it works for you, and its extensive capabilities will have you covered no matter your use case.

DbVisualizer is a neat SQL client that gives you the ability to dig into any databases you may find yourself running at the time (and yes, it also displays all available storage engines available for you to use):

DbVisualizer displaying databases and storage engines in MariaDB
DbVisualizer displaying databases and storage engines in MariaDB

Take DbVisualizer for a spin today, follow our blog at TheTable, and we’ll see you in the next one. Bye for now.

Summary

Parsing and SQL data types often are an inseparable pair because we need to choose data types that we are going to use carefully before proceeding with any data parsing. Some use cases may require you to parse data offline and import data into a live system afterwards, but regardless, we hope that this blog post has helped you understand some of the decisions developers make when choosing data types in SQL.

FAQ

What are data types in SQL?

In SQL, data types refer to a set of data types available in your database management system of choice that has a direct impact on how you store data in your databases and tables. The length of the data types also has a direct impact of how many characters you can store in a specific column, though this capability is deprecated in some newer versions of relational database management systems.

What is Data Parsing?

In simple words, data parsing refers to a process of converting and/or analyzing data into a specific format applicable to your use case.

Where Can I learn more about parsing data into SQL data types?

To learn more about data types and parsing in SQL, consider reading blogs like TheTable, attending industry conferences or workshops, or reading books about your database management system of choice. For users of MySQL, Hacking MySQL: Breaking, Optimizing, and Securing MySQL for Your Use Case should be a good place to start.

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About the author
LukasVileikisPhoto
Lukas Vileikis
Lukas Vileikis is an ethical hacker and a frequent conference speaker. He runs one of the biggest & fastest data breach search engines in the world - BreachDirectory.com, frequently speaks at conferences and blogs in multiple places including his blog over at lukasvileikis.com.
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