When you should and should not use NoSQL databases
Different Store
Viewed at an abstract level, very much of what is known revolves around the relationship of two or more things to each other: events to dates, nuclear charges to chemical properties, items to prices, authors to works, and so on. Rows and columns in a table are an obvious way of mapping these relationships. The ancient Greeks were literally already aware of this advantage – Ptolemy started recording astronomical observations in tabular form in the second century. Since then, the table has triumphed in all areas of life, from religion, where the description of the same events in different gospels was recorded in tabular form centuries ago (canon tables), to music, where musical notation can be understood as a table in which the bar lines mark the columns and the staves the rows.
When the search for efficient ways to manage large amounts of data began in computer science in the 1970s, spreadsheets were used. Edgar F. Codd developed the relational database model and the forerunner of the SQL query language. Both still exist today, with the relational database management system (RDBMS) still dominating the market as the top four most popular databases (DBs) in November 2024: Oracle, MySQL, Microsoft SQL Server, and PostgreSQL [1]. So why look for alternatives when traditional database technology uses such a universal basic form of information storage?
Specialist Data
Not everything can be recorded in a table, including unstructured data (e.g., text), for which the elements of a statement are not broken down into individual attributes and their values. In turn, this means they cannot simply be assigned to rows and columns, which makes tables unsuitable in this case. Similarly, tables are not recommended where the type and number of attributes to be stored vary greatly. Because the relational model works with a database schema that creates
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