OLAP (Online Analytical Processing) is a category of database processing that facilitates business intelligence.
OLAP provides analysts, managers, and executives with the information they need to make effective decisions about an organization’s strategic directions. OLAP can provide valuable insights into how their business is performing, as well as how they can make improvements.
OLTP (Online Transactional Processing) is a category of data processing that is focused on transaction-oriented tasks. OLTP typically involves inserting, updating, and/or deleting small amounts of data in a database.
OLTP mainly deals with large numbers of transactions by a large number of users.
Normalization is the process of organizing a database to reduce redundancy and improve data integrity.
Normalization also simplifies the database design so that it achieves the optimal structure composed of atomic elements (i.e. elements that cannot be broken down into smaller parts).
Also referred to as database normalization or data normalization, normalization is an important part of relational database design, as it helps with the speed, accuracy, and efficiency of the database.
The Third Manifesto is a detailed proposal for the future direction of data and database management systems (DBMSs).
Written by C.J. Date and Hugh Darwen, The Third Manifesto can be viewed as a blueprint for the design of future DBMSs, as well as any language designed to interface with them.
Codd’s 12 rules is a set of rules that a database management system (DBMS) must satisfy if it’s to be considered relational (i.e. a relational DBMS).
The rules were proposed by Edgar F. Codd, who is considered a pioneer of the relational database model.
Codd’s 12 rules is actually a set of thirteen rules, numbered from zero to twelve. The twelve rules are based on a single foundation rule — Rule Zero.
There’s a lot of confusion regarding the difference between an RDBMSs and a DBMS. I’ve even seen “RDBMS vs DBMS” forum posts where the accepted answer outlines the differences between RDBMSs and DBMSs, as though they were two distinct and different things.
However, this can be misleading.
The fact is, an RDBMS is a DBMS. But a DBMS is not always an RDBMS (but it often is).
So, is there a difference between an RDBMS and a DBMS or not? Is “RDBMS vs DBMS” the right way of looking at it, or is there more to it?
NoSQL databases are often categorised under four main types. Some databases are a mix between different types, but in general, they fit under the following main categories.
A column store database is a type of database that stores data using a column oriented model.
A column store database can also be referred to as a:
- Column database
- Column family database
- Column oriented database
- Wide column store database
- Wide column store
- Columnar database
- Columnar store
Column store databases are considered NoSQL databases, as they use a different data model to relational databases.
A document store database (also known as a document-oriented database, aggregate database, or simply document store or document database) is a database that uses a document-oriented model to store data.
Document store databases store each record and its associated data within a single document. Each document contains semi-structured data that can be queried against using various query and analytics tools of the DBMS.
A key-value database (also known as a key-value store and key-value store database) is a type of NoSQL database that uses a simple key/value method to store data.
The key-value part refers to the fact that the database stores data as a collection of key/value pairs. This is a simple method of storing data, and it is known to scale well.