SQL vs NoSQL Databases: How to Choose
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
A compact pattern language used to search, match, and manipulate text, such as finding email addresses or validating phone numbers.
A regular expression, often called regex, describes a pattern of characters. Special symbols represent ideas such as any digit, one or more repetitions, or the start of a line. Most programming languages, text editors, and databases support regular expressions.
For example, a simple pattern can match postal codes made of six digits, or find every line in a log file that contains an error code. Developers use regex for form validation, data cleaning, search and replace, and parsing structured text. Regular expressions are powerful but notoriously hard to read, and complex patterns can be slow or behave unexpectedly. Some poorly written patterns can even be exploited to overload a server. For complicated formats such as HTML or full email validation, dedicated parsers are usually safer.
A finite, well-defined sequence of steps for solving a problem or performing a computation.
Data CleansingFinding and correcting errors, duplicates, and inconsistencies in data so it is accurate and usable for analysis.
DebuggingThe process of finding, understanding, and fixing errors, or bugs, in software code.
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
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