String splitting in SQL isn't a built-in function in most standard SQL databases. Instead, you need to use string functions like SUBSTRING, CHARINDEX, and a loop or recursive CTE to achieve this. This approach allows you to manipulate and extract data from strings based on delimiters.
String splitting in SQL isn't a single, straightforward function like some other languages might offer. Most SQL databases don't have a built-in function to directly split strings. This means you need to use a combination of string functions to achieve the desired result. These functions, such as SUBSTRING and CHARINDEX, allow you to extract portions of a string based on positions or delimiters. A common approach involves using a loop or a recursive Common Table Expression (CTE) to iterate through the string and extract each segment. This process is often necessary when dealing with data stored in a single string field that needs to be parsed into multiple columns or rows. For example, a log file might store multiple events in a single line, separated by a comma. String splitting allows you to extract each event into a separate row for analysis.
String splitting is crucial for data manipulation and analysis. It allows you to transform data stored in a single field into a structured format, making it easier to query and analyze. This is essential for tasks like extracting information from log files, CSV data, or any data source where information is concatenated.
When your database lacks a dedicated SPLIT function, the usual workaround is to chain SUBSTRING (or LEFT/RIGHT) with CHARINDEX (or POSITION/INSTR). CHARINDEX locates the delimiter position, while SUBSTRING extracts the fragment before or after it. By repeating this logic you can peel off each segment until the full string has been parsed.
Because the number of segments in a string is rarely fixed, you need a construct that can iterate until no delimiter remains. A WHILE loop achieves this procedurally, whereas a recursive Common Table Expression (CTE) offers a set-based alternative that successively removes the first token and recurses on the remainder. Both approaches turn one row with a delimited field into many rows, making downstream analysis or joins much simpler.
Galaxy understands the schema and your coding patterns, so you can ask it to “split the events column on commas” and it will instantly generate an optimized loop or recursive CTE tailored to your dialect (PostgreSQL, SQL Server, etc.). It can even refactor existing queries when the delimiter changes, saving engineers from manually rewriting SUBSTRING/CHARINDEX logic and letting teams share the vetted solution through Galaxy Collections.