Limitations of the relational model

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Limitations of the relational model

Limitations of the relational model

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Overview

application areas for which the relational model is inadequate - reasons

drawbacks of relational DBMSs

Limitations of the relational model

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Areas needing advanced database systems

both in terms of structure of data and of operations to be performed on data computer aided design (CAD) computer aided manufacturing (CAM) computer aided software engineering (CASE) office information systems, multimedia systems and digital

publishing geographic information systems etc.

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CAD

what is CAD? do you think CAD needs database systems? imagine you were going to use a relational DBMS

(e.g. Postgres) to support a CAD application; what difficulties do you think you wold encounter?

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CAD - characteristics | insufficiency of relational database systems

characteristic problemdesigns - large number of types(millions, sometimes); smallnumber of instances

not suitable for relational model;why?

designs - many interdependenciesbetween subsystems

interdependency integrityconstraint; the relational modeldoes not provide sufficientsupport for integrity constraints

design evolves through time -implications must be propagated;some actions cannot be ‘a priori’foreseen

schema evolution plus integrityconstraints modifications basedon the new schema

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CAD - characteristics | insufficiency of relational database systems

characteristic problemupdates are far reaching; onechange (usually) affects a largenumber of objects

integrity constraints

design alternatives; versions no support

co-operative engineering = manystaff work in parallel on multipleversions of the same product; theend product must be consistentand co-ordinated

no support

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CAD and relational databases

could you solve any of the problems mentioned, basing your solution solely on features of relational database systems?

the answer is yes, but some of the features you are using in your solutions are (probably) not implicit in the relational model

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CAM

similar to CAD but more data processing required monitoring control

possibly, both in real time

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CASE - characteristics that make it unsuitable for the relational model

(large) data relating to the stages of the software development lifecycle

co-operative engineering concurrent sharing of project design, code and

documentation; dependencies between components must be tracked

project management scheduling cost estimation progress monitoring

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Office Information Systems and Digital Publishing

characteristic problemwide range of data types (e.g.multimedia types: pictures,sound, video)

not supported; data cannot bestored or it cannot beaccessed “inside”

data is shared (retrieve andupdate) among many users;

the simple locking of a wholedocument - not sufficient;some versioning system maybe required

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Geographic information systems

spatial information - not supported by relational DBMSs

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Drawbacks of relational databases

poor representation of real world entities semantic overloading poor support for integrity constraints homogeneous data structure limited operations difficulty in handling recursive queries impedance mismatch other problems ...

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Poor representation of real world objects

normalisation -> fragmentation relations that have no correspondent in the real world to infer information -> joins -> very costly

poor semantics everything is a RELATION (see next slide)

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Semantic overloading

no distinction between entity and relationship; no distinction between different types of relations (e.g. “has” “is the parent of”, “has the address”, “is located”, “earns”)

result: this semantic cannot be expressed (e.g. be build into the operators)

there is very little meaning in relations (i.e. the systems “knows” very little of the data it contained); what solutions to increase the semantics exist?

domains - provided by the relational model, but not fully supported by relational DBMSs

keys - provided and supported support for enterprise integrity constraints …?

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Poor support for integrity constraints

integrity validity and consistency entity integrity + referential integrity + domains

many systems do not fully support -> build them into applications -> effort + inconsistencies

integrity is expressed in terms of constraints (rules that the database must comply with) the constraint checking mechanism is simple

degree of compliance; categories of integrity constraints ...

what does it mean must comply with? what is the logical model? must be deduced from the DB? the DB must

be consistent with them?must be true of the DB?

the relational model does not support enterprise integrity constraints SQL provides support for constraints as part of the DB def.

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Homogeneous data structure

horizontal and vertical homogeneity too restrictive real world objects have a more complex structure result: unnatural structures + many joins (inefficient) example: composite parts on the other hand, this symmetric structure is one of the

strengths of the relational model (why?) binary large objects (BLOB)

are allowed typically, they are references to files, therefore some

advantages provided by DBMSs may be lost (e.g. security) their inner structure cannot be accessed

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Limited set of operations

only a fix set operations tuple oriented set oriented

not sufficient for many applications (e.g. geographic information systems - distance, area, …)

no new operations cannot be specified some DBMSs allow for type extensibility

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Difficulty in handling recursive queries

Staff_no Manager_staff_no

S5 S4S4 S3S3 S2S2 S1S1 NULL

Staff_no Manager_staff_no

S5 S4S5 S3… …S5 S1S4 S3… …S3 S2S3 S1S2 S1S1 NULL

Transitive closure

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Impedance mismatch

SQL92 lacks computational completeness solution: embedded SQL drawback of solution: impedance mismatch

mixing different paradigms SQL: set based operators high level programming languages: record based

(or even less) (example C) conversion to records needed (inefficient!)

type mismatch solution by Date: build set level facilities in high level

programming languages

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Other problems

other problems also exist no support for long lived transactions (not inherent to the relational

model) schema amendments - difficult poor navigational access

therefore, other approaches might be needed

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Conclusions

first generation DBMSs 1060s-1970s two approaches: hierarchical and network main problems: complex programs needed to be written to

answer simple queries (navigational databases); minimal data independence; no widely accepted theoretical foundations

second generation 1970 - Codd’s paper 1970-1980 - many experimental relational DBMSs now: over 100 commercial DBMSs (some stretch the definition

of a relational DBMS)

third generation … (“to be continued”)