PUBLIC MARKS from ogrisel with tag database

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This is a set of rules of thumb for setting up your PostgreSQL 8.0 server. A lot of the below is based on anecdotal evidence or practical scaling tests; there's a lot about database performance that we, and OSDL, are still working out. However, this should get you started. All information below is useful as of January 12, 2005 and will likely be updated later. Discussions of settings below supercede the recommendations I've made on General Bits.

Relational databases are universally conceived of as an advance over their predecessors network and hierarchical models. Superior in every querying respect, they turned out to be surprisingly incomplete when modeling transitive dependencies. Almost every couple of months a question about how to model a tree in the database pops up at the comp.database.theory newsgroup. In this article I'll investigate two out of four well known approaches to accomplishing this and show a connection between them. We'll discover a new method that could be considered as a "mix-in" between materialized path and nested sets.

First mail of a thread on the postgresql mailing list dealing of various ways to implement a tree structure with PostgreSQL.

This document describes an approach for handling hierarchical data in a relational database.

The fundamental objective for a relational database management system (RDBMS) is to keep data independent of the applications or analysis that use it. (Date, C. J., An Introduction to Database Systems, Seventh Edition, Chapter 1) There are two reasons for this: * Different applications require different views of the same data. * Data must be extendable and new applications and analysis introduced without having to modify existing applications.

Denormalization is the process of attempting to optimize the performance of a database by adding redundant data. It is sometimes necessary because current DBMSs implement the relational model poorly. A true relational DBMS would allow for a fully normalized database at the logical level, while providing physical storage of data that is tuned for high performance.

Heuristics for denormalizing relational database tables are examined with an objective of improving processing performance for data insertions, deletions and selection. Client-server applications necessitate consideration of denormalized database schemas as a means of achieving good system performance where the client-server interface is graphical (GUI) and the network capacity is limited by the network channel.