IB Computer Science Topic A3: Databases Key Definitions

The four guarantees a database makes about every transaction: atomicity, consistency, isolation and durability. Together they ensure that grouped operations are processed reliably and leave the data in a valid state.

A SQL function that reads the values of a column across many rows and returns one summary value. The five named in the syllabus are AVERAGE (written AVG in most systems), COUNT, MAX, MIN and SUM.

The tools and practices an organisation uses to query its stored data and turn the results into decisions, covering decision support, trend analysis, forecasting and performance monitoring.

The maximum number of instances of one entity that can be linked to a single instance of another entity, which is either one or many. It is read separately for each end of a relationship line, giving the shapes 1:1, 1:N and M:N.

A database hosted and run on a provider's remote servers rather than on hardware the organisation owns. The provider supplies capacity on demand and handles backups, patching, security and maintenance.

Clustering is a technique used to group a set of objects so that objects in the same group (or cluster) are more similar to each other than to those in other groups.

A composite key is a primary key that consists of two or more columns.

The highest-level description of a database, naming the entities it must store and the relationships between them. It carries no attributes, keys, data types or storage detail.

The subset of SQL that defines and changes the structure of a database, using commands such as CREATE, ALTER, DROP, TRUNCATE and RENAME. DDL acts on database objects rather than on the rows stored inside them.

The subset of SQL that works with the rows held in a structure that already exists, using SELECT, INSERT, UPDATE and DELETE. DML cannot change the definition of a table.

The storing of copies of the same data at more than one site in a distributed database, which improves read performance and availability at the cost of keeping every copy up to date.

A central store that collects historical data from an organisation's operational systems and holds it in a form designed for analysis rather than for running the business.

The structure of a database: the tables it holds, the attributes in each table, the relationships between them, and the constraints the data must obey. A schema defines organisation only and stores no records of its own.

A named SELECT statement stored in the database and queried like a table, returning data drawn from one or more base tables.

Deadlock occurs when processes are stuck waiting for resources held by each other.

Denormalization is the process of intentionally introducing redundancy into a normalized database to improve performance.

A database whose data is stored across several physical sites, often on separate machines or in separate locations, while presenting itself to users and applications as a single logical database.

The property of a distributed database that hides how and where data is stored, so users and applications work with it as one database without knowing which site holds any given item.

A diagram of a database design that shows each entity, the attributes it stores, and the relationships between entities, with the cardinality and modality of every relationship marked on the line.

The scheduled three-stage process that fills a data warehouse: data is extracted from each source system, transformed into the warehouse's agreed formats, and loaded in as new rows.

A foreign key is a column (or set of columns) in one table that references the primary key of another table.

Attribute B is functionally dependent on attribute A if every value of A gives exactly one value of B. The dependency runs one way only, so A determines B does not mean B determines A.

A database that holds its working data in RAM rather than on disk, so reads and writes avoid the slowest step in the storage hierarchy. The contents are lost when power is lost unless a disk log or non-volatile memory is used.

A join combines rows from two tables into one result by matching values in a column they share, normally a foreign key in one table and the primary key it refers to in the other.