network model (data)

network model (data)
Name	Network model (data)
Type	Database model
Introduced	1960s
Parent	Database models
Related	Relational model, Hierarchical model, Graph theory

network model (data) The network model (data) is a database paradigm that organizes records as interconnected sets of nodes and edges, permitting many-to-many relationships and direct navigation among records. Originating in the mid-20th century, it contrasted with the hierarchical model and preceded widespread adoption of the relational model in computer science. The model influenced standards and implementations across IBM, Honeywell, and educational institutions such as the University of California, Los Angeles and Massachusetts Institute of Technology.

Definition and Overview

The network model defines data in terms of records linked by explicit sets or pointers, enabling traversal akin to graphs and network analysis. It supports complex relationships similar to those studied at Bell Labs and in work by Charles Bachman at General Electric, who won the Turing Award for contributions that led to the CODASYL specifications. Implementations expose operations for navigating from one record to related records, resembling techniques used in graph database systems and reflecting concepts from Erdős–Rényi model studies.

Historical Development

The model evolved from research at General Electric, IBM, and academic centers during the 1960s and 1970s, formalized by the Conference on Data Systems Languages (CODASYL) committee and presented alongside competing proposals from Edgar F. Codd at IBM Research. Early commercial systems from Honeywell and Burroughs Corporation adopted network-like access methods, while standards work occurred within ANSI and ISO technical committees. Debates between proponents of the network model and advocates of the relational model culminated in shifts in industry practice influenced by events like the rise of Oracle Corporation and publications from Berkeley and Stanford researchers.

Data Structures and Representation

Network-model databases represent records using structures such as records, pointers, and set types that form directed or undirected links akin to edges in graph theory. Logical schemas define record types and owner-member set relationships, comparable to entity types in Entity–relationship model diagrams used at MIT. Physical storage strategies mirror file organization methods studied at Carnegie Mellon University, employing techniques related to B-tree indexing and block allocation from UNIX file system research at Bell Labs.

Operations and Querying

Typical operations include creation, deletion, and traversal of owner-member sets, plus position-based navigation analogous to cursor operations in SQL-based systems like PostgreSQL and MySQL. Querying often uses network-specific data manipulation languages defined by CODASYL standards, contrasted with declarative Structured Query Language introduced by ANSI and popularized by vendors such as IBM and Microsoft. Optimization strategies for traversal borrow from algorithmic work at Princeton University and University of Illinois on shortest-path and graph-search methods, relevant to runtime performance on mainframes from IBM and minicomputers from DEC.

Applications and Use Cases

Historically, the network model served transaction-heavy applications in banking systems at institutions like Barclays and First National Bank implementations, telecommunication switching databases at companies such as AT&T and Siemens, and manufacturing resource planning at firms including Ford Motor Company and General Motors. It also underpinned reservation systems at American Airlines and inventory control at Walmart-class retailers. Concepts from the model inform modern social network analysis at Facebook and Twitter and concepts applied in bioinformatics projects at Harvard Medical School and The Salk Institute.

Comparison with Other Models

Compared with the relational model articulated by Edgar F. Codd at IBM Research, the network model emphasizes pointer-based navigation and explicit many-to-many relationships, whereas the relational approach uses set-theoretic tables and declarative SQL queries, championed by organizations like Oracle Corporation and Sybase. Relative to the hierarchical model deployed in systems like IBM IMS, the network model allows more flexible schemas similar to contemporary graph database platforms from companies such as Neo4j and TigerGraph. Academic comparisons in journals from ACM and IEEE often cite trade-offs in concurrency control, normalization, and schema evolution.

Implementation and Performance Considerations

Implementations must manage pointer integrity, concurrency, and recovery, drawing on transaction research from ACM SIGMOD and IFIP working groups. Performance depends on storage layout, indexing strategies like variations of B+ tree and hashing, and buffer management techniques developed at University of California, Berkeley and Stanford University. Scaling across distributed systems invokes protocols and middleware from Sun Microsystems and research on distributed transactions at Google and Amazon Web Services, while modern reinterpretations adopt graph-processing frameworks such as Apache Giraph and GraphX from the Apache Software Foundation.

Category:Database models