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.

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.

Relational (SQL) databases store data in tables with strictly-defined relationships between tables. Non-relational (NoSQL) databases are more flexible and allow for less organized and less ...

mcp_ohmy_sql is an open-source Text-to-SQL system developed for deployment in enterprise production. It is not about specific ...

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 ...

A relational database is a set of formally described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The standard user ...

PostgreSQL implementation of document-oriented NoSQL datastore adopted under permissive MIT license The Linux Foundation on ...

Most every business database management system (DBMS), including Oracle, DB2, SQL Server, MySQL, etc., is a relational DBMS (RDBMS) (see DBMS). Hierarchical, Network and Object Databases ...

It’s not NoSQL, it’s post-relational by Adam Keys, software developer and writer, on The Real Adam blog, August 2009. The Future Is Big Data in theCloud, by Ping Li, Accel Partners.