An Introduction to Database Systems¶
Date, C. J. (2003). An Introduction to Database Systems. Addison-Wesley.
Cited by¶
12 citations across 12 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Consistency
- Databases and distributed systems. The constraints of a schema — uniqueness, referential integrity, business rules — must not jointly forbid any state the system is meant to record, and a transaction commits only if the resulting state respects every invariant.
This sourceDefines integrity constraints, referential integrity, and the requirement that a transaction commit only into a consistent state.
- Databases and distributed systems. The constraints of a schema — uniqueness, referential integrity, business rules — must not jointly forbid any state the system is meant to record, and a transaction commits only if the resulting state respects every invariant.
- Criteria of Individuation
- In database and information systems, the three criteria are engineered explicitly: a primary key is a stipulated identity criterion (two rows are the same entity iff they share a key), entity resolution and master-data management reconstruct co-reference where no shared key exists, transaction and document boundaries fix unity, and the chosen primary kind fixes persistence — together determining how many distinct customers, patients, or documents the system believes exist.
This sourceStandard relational-database text defining the primary key as the stipulated identity criterion enforcing entity integrity (each tuple uniquely identified; two rows are the same entity iff they share the key), with master-data/entity-resolution reconstructing co-reference where no shared key exists.
- In database and information systems, the three criteria are engineered explicitly: a primary key is a stipulated identity criterion (two rows are the same entity iff they share a key), entity resolution and master-data management reconstruct co-reference where no shared key exists, transaction and document boundaries fix unity, and the chosen primary kind fixes persistence — together determining how many distinct customers, patients, or documents the system believes exist.
- Disjointness
- In database design, partitioned tables, shard keys, and primary keys all enforce disjointness, and
UNION ALLequalsUNIONonly when the sources are disjoint.This sourceStandard relational-database reference covering primary keys, partitioning, and the set operators, including the requirement that UNION ALL coincides with UNION only when the source relations are disjoint (share no tuples). ISBN 9780321197849.
- In database design, partitioned tables, shard keys, and primary keys all enforce disjointness, and
- Identifier Assignment
- The handle is the primary key itself, drawn from a defined shape (a 64-bit integer or a 128-bit UUID) and deliberately opaque: it is not derived from the entity's mutable attributes, so it survives a name change, an address change, or a status change.
This sourceStandard text establishing surrogate (opaque) primary keys decoupled from mutable attributes and referential integrity, and the anti-pattern of using a natural key (email, phone) that breaks on change.
- The handle is the primary key itself, drawn from a defined shape (a 64-bit integer or a 128-bit UUID) and deliberately opaque: it is not derived from the entity's mutable attributes, so it survives a name change, an address change, or a status change.
- Intersection
- In software and data engineering it is the SQL inner join, the type intersection
A & B, the set of package versions satisfying every dependency, and the access rule requiring all roles to grant entry.This sourceStandard reference for relational algebra, including INTERSECT and the inner join as a set-intersection-style conjunction of membership conditions.
- In software and data engineering it is the SQL inner join, the type intersection
- Persistent Identifier
- In databases it is surrogate keys — opaque, system-assigned — chosen over natural keys precisely to insulate references from natural-key change, with foreign keys as the inter-table version of the same discipline.
This sourceStandard treatment of surrogate versus natural keys, foreign-key referential integrity, and why opaque system-assigned keys insulate references from attribute change.
- In databases it is surrogate keys — opaque, system-assigned — chosen over natural keys precisely to insulate references from natural-key change, with foreign keys as the inter-table version of the same discipline.
- Predicate
- In computing the filter clause of a query is a predicate over rows, a function's type specifies predicates its inputs must satisfy, and assertions and invariants are predicates evaluated at runtime or proof-time.
This sourceTreats the relational model and query predicates (WHERE clauses) as truth-valued tests over rows.
- In computing the filter clause of a query is a predicate over rows, a function's type specifies predicates its inputs must satisfy, and assertions and invariants are predicates evaluated at runtime or proof-time.
Domain-specific¶
Mechanisms¶
- Constraint Gate Enforcement
- Its strength is a guarantee that holds regardless of who is calling: if the constraint is enforced at the boundary of record, no path can plant an inadmissible value, which is why referential integrity
This sourceDefines database integrity constraints as schema-level conditions that must remain true, including referential constraints that prevent unmatched foreign-key values regardless of the calling application.
- Its strength is a guarantee that holds regardless of who is calling: if the constraint is enforced at the boundary of record, no path can plant an inadmissible value, which is why referential integrity
- Denormalized Field Generation
- It misleads when the copied field actually changes often — every origin update now fans out to every copy
This sourceExplains that redundant copies require coordinated updates and can reintroduce the update anomalies normalization addresses.
- It misleads when the copied field actually changes often — every origin update now fans out to every copy
- Prejoined Read Table
- Because a source value is duplicated across many rows, an update must fan out to all of them, and if that fan-out is incomplete or lags, the table exhibits an update anomaly
This sourceExplains that redundant facts repeated across rows require multi-row updates and can become inconsistent when an update is incomplete.
- Because a source value is duplicated across many rows, an update must fan out to all of them, and if that fan-out is incomplete or lags, the table exhibits an update anomaly
Verification¶
Does it exist? Confirmed. This work's ISBN resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Not recorded. Neither this nor any other of the 12 citations of this work carries a recorded support check.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Links previously used in the corpus¶
Before the registry existed this work was also linked 5 other ways.
- https://openlibrary.org/isbn/9780321197849 ×3
- https://openlibrary.org/books/OL9422130M/An_Introduction_to_Database_Systems ×2
- https://www.pearson.com/en-nz/subject-catalog/p/introduction-to-database-systems-an/P200000003393/9780321197849 ×2
- https://www.pearson.com/en-us/subject-catalog/p/introduction-to-database-systems-an/P200000003393 ×1
- https://www.worldcat.org/oclc/52086932 ×1
Registry ID ref:98e86ef0915a · see in the full table