Relational databases for operations on large data sets are contraindicated because SQL queries tend to consume many CPU cycles and thrash the disk as they process data.

Even with all the hype around NoSQL, traditional relational databases still make sense for enterprise applications. Here are four reasons why.

Learn about and revise the topics of relational databases and structured query language (SQL) with this BBC Bitesize GCSE Computer Science AQA study guide.

Indexing is a critical part of database optimization. Indexing can dramatically increase query speed. However, DBAs still struggle with finding optimal indexes or optimal SQL plans. DBTA held a ...

Learn More. Startup Vembu Technologies has unveiled an SQL conversion tool thats designed to parse any relational database dialect and automatically convert SQL queries into other SQL dialects.

These provide some of the things that SQL-based relational databases do but are tuned heavily for handling the demands of big data. VoltDB falls into this category: it's a high-speed SQL database.

With data relationships at their center, graph databases are highly efficient when it comes to query performance, even for deep and complex queries.

SQL is about as easy as it gets in the world of programming, and yet its learning curve is still steep enough to prevent many people from interacting with relational databases. Salesforce's AI ...

If the history of relational databases is any indication, what is going on in graph databases right now may be history in the making.