SQL vs NoSQL: How to Choose

In the previous article we discussed the primary differences between SQL and NoSQL databases. In this follow-up, we'll apply our knowledge to specific scenarios and determine the best option.

To recap:

SQL databases:

• store related data in tables
• require a schema which defines tables prior to use
• encourage normalization to reduce data redundancy
• support table JOINs to retrieve related data from multiple tables in a single command
• implement data integrity rules
• provide transactions to guarantee two or more updates succeed or fail as an atomic unit
• can be scaled (with some effort)
• use a powerful declarative language for querying
• offer plenty of support, expertise and tools

NoSQL databases:

• store related data in JSON-like name-value documents
• can store data without specifying a schema
• must usually be denormalized so information about an item is contained in a single document
• should not require JOINs (presuming denormalized documents are used)
• permit any data to be saved anywhere at anytime without verification
• guarantee updates to a single document -- but not multiple documents
• provide excellent performance and scalability
• use JSON data objects for querying
• are a newer, exciting technology

SQL databases are ideal for projects where requirements can be determined and robust data integrity is essential. NoSQL databases are ideal for unrelated, indeterminate or evolving data requirements where speed and scalability are more important.

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by Craig Buckler via SitePoint