A relational database is a type of structure organizing data into groups through tables, that contain rows and columns. These tables connect by keys associated with each row in other tables.
Data in any relational database can be added to, viewed, filtered, modified or deleted through a standard programming interface called structured query language (SQL). SQL provides the foundation in relational database usage, including forms to interact with the data (e.g. searching data, entering in new data) and reports (displaying results).
The relational database structure has been around since the 1970s and continues to be in use today.
“IDC forecasts that relational DBs will still account for more than 80% of the total operational database market through 2022 and Gartner forecasts that through 2020, relational technology will continue to be used for at least 70% of new applications and projects.”
Relational databases are typically found in data warehouses.
Other Definitions of Relational Databases Include:
- “A depiction based on set theory and relational algebra, where data elements or attributes (columns) are related to tuples (rows).”(DAMA-DMBOK2)
- “An arrangement, invented by Edgar F Codd in 1970, where data is arranged into different rows and columns by associating a specific key for each row.” (Keith D. Foote)
- A database that is” organized and accessed according to the relationships between data items”. These relationships are expressed by tables. (Gartner IT Glossary)
- “A database comprised of multiple connected tables.” (MIT Information Systems and Technology Knowledge Base)
Relational Database Use Cases Include:
- A company who tracks customer accounts.
- A business wishes to recommend products to customers and uses a relational database with automated machine learning to make this happen
- A company needs to track medical equipment and stores this information in relational databases
- An application manages user profiles through a relational database.
- A content management system
Businesses Use Relational Databases to:
- Support business-critical systems operations like provisioning, patching, backing up, etc.
- Support general business operations like customer payments and bank accounting
- Store data more efficiently
- Manage huge amounts of mission-critical customer information.
- Analyze business data
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