RDBMS

A relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by E. F. Codd, of IBM's San Jose Research Laboratory. Many popular databases currently in use are based on the relational database model.

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According to research company Gartner, the five leading commercial relational database vendors by revenue are Oracle (48.8%), IBM (20.2%), Microsoft (17.0%), SAP including Sybase (4.6%), and Teradata (3.7%).

HISTORY

In 1974, IBM began developing System R, a research project to develop a prototype RDBMS.^[4] Its first commercial product was SOL/DS, released in 1981.^[5] However, the first commercially available RDBMS was Oracle, released in 1979 by Relational Software, now Oracle Corporation.^[6] Other examples of an RDBMS include DB 2, SAP Sybase ASE, and Informix.

COMPARISON BETWEEN TRADITIONAL AND infiniSQL ARCHITECTURE

TYPES OF RDBMS

• Hierarchical RDBMS
• Network RDBMS
• Relational RDBMS
• Object-Oriented RDBMS

   Hierarchical RDBMS

   

A DBMS is said to be hierarchical if the relationships among data in the database are established in such a way that one data item is present as the subordinate of another one or a sub unit. Here subordinate means that items have "parent-child" relationships among them. Direct relationships exist between any two records that are stored consecutively. The data structure "tree" is followed by the DBMS to structure the database. No backward movement is possible/allowed in the hierarchical database.

 Network RDBMS

A DBMS is said to be a Network DBMS if the relationships among data in the database are of type many-to-many. The relationships among many-to-many appears in the form of a network. Thus the structure of a network database is extremely complicated because of these many-to-many relationships in which one record can be used as a key of the entire database. A network database is structured in the form of a graph that is also a data structure. Though the structure of such a DBMS is highly complicated however it has two basic elements i.e. records and sets to designate many-to-many relationships. Mainly high-level languages such as Pascal, C++, COBOL and FORTRAN etc. were used to implement the records and set structures

Relational RDBMS

A DBMS is said to be a Relational DBMS or RDBMS if the database relationships are treated in the form of a table. There are three keys on relational DBMS: relation, domain and attributes. A network means it contains a fundamental constructs sets or records sets contains one to many relationship,records contains fields statical table that is composed of rows and columns is used to organize the database and its structure and is actually a two dimension array in the computer memory. A number of RDBMS are available, some popular examples are Oracle, Sybase, Ingress, Informix, Microsoft SQL Server, and Microsoft Access.

Object-Oriented RDBMS

Able to handle many new data types, including graphics, photographs, audio, and video, object-oriented databases represent a significant advance over their other database cousins. Hierarchical and network databases are all designed to handle structured data; that is, data that fits nicely into fields, rows, and columns. They are useful for handling small snippets of information such as names, addresses, zip codes, product numbers, and any kind of statistic or number you can think of. On the other hand, an object-oriented database can be used to store data from a variety of media sources, such as photographs and text, and produce work, as output, in a multimedia format.

Transaction Processing

Transaction processing details are described in the overview. What I discovered implementing ACID capabilities using actors is that other techniques needed to be implemented as well. Namely, inter-actor remote procedure calls (RPC), a home-grown protocol stack inspired loosely on the OSI model, and continuations. This introduces a certain amount of implementation complexity--I'm on the lookout for ways to refactor and decrease complexity. But all of the ACID characteristics (except for Durability, as described above) are functional.

Row Based, Tables, Indices

The actor-based core and transaction processing capabilities could work with any number of different types of databases. Column-based, simple keystores, XML doc stores, graphdb's. Anything that needs to scale and benefits from parallelism. But I chose to implement a row-based RDBMS as the first underlying storage scheme for InfiniSQL. In spite of the other types, this model still support a huge variety of applications. Most of the alternate data organization types are optimized for a particular type of workload--and abysmal at others. Column data stores aren't suited for transaction processing, for instance. Keystores can't really do anything other than get/set simple objects. There's nothing earth-shatteringly innovative about the way that InfiniSQL organizes and manipulates data, but the underlying architecture overcomes many of the limitations that drove adoption of many alternate database types.

PostgreSQL clients are used to perform SQL queries, so really any platform and language should be able to use InfiniSQL. They've documented the Front-end/Back-end Protocol very well, so implementing it for InfiniSQL has been pretty simple. (InfiniSQL and PostgreSQL are completely separate projects.)

QUERY AND NO-QUERY

DATABASE DESIGN SPACE

Summary

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