In database systems, ACID (Atomicity, Consistency, Isolation, Durability) refers to a standard set of properties that guarantee database transactions are processed reliably.
ACID is especially concerned with how a database recovers from any failure that might occur while processing a transaction.
An ACID-compliant DBMS ensures that the data in the database remains accurate and consistent despite any such failures.
Oracle Database is an object-relational database management system (ORDBMS) produced by Oracle Corporation. It is one of the world’s most popular database management systems (DBMSs).
Oracle Database is often shortened to “Oracle” and sometimes “Oracle DB” or “Oracle RDBMS” (although it’s not the only product from Oracle Corporation).
PostgreSQL is an object-relational database management system (ORDBMS). It is an open source system that is known for its close alignment with the SQL standard.
PostgreSQL is one of the world’s most popular database management systems (DBMS), and it is consistently in the top 5 on the DB-Engines ranking list.
Graph databases have been gaining popularity over recent years as a viable alternative to the relational model. Graph databases are particularly well suited to storing connected data – data with lots of interconnected relationships, especially those that run many levels deep.
This article looks at the main differences between graph databases and relational databases.
A graph database is a database that uses a graphical model to represent and store the data.
The graph database model is an alternative to the relational model.
In a relational database, data is stored in tables using a rigid structure with a predefined schema.
In a graph database, there is no predefined schema as such. Rather, any schema is simply a reflection of the data that has been entered. As more varied data is entered, the schema grows accordingly.
An MPP database is a massively parallel processing database (MPP stands for Massively Parallel Processing).
Massively parallel processing refers to the use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel (simultaneously).
ORDBMS stands for Object-Relational Database Management System.
An ORDBMS is a database management system that is a hybrid between the object-oriented model (OODBMS) and the relational model (RDBMS).
Each of those two models has their strengths and weaknesses. By combining the two models, a DBMS can take advantage of various strengths from each model.
OODBMS stands for Object-Oriented Database Management System.
An object-oriented database management system (also known simply as an object database) is a DBMS where data is represented in the form of objects, as used in object-oriented programming.
In contrast to relational database management systems (RDBMSs), where data is stored in tables with rows and columns, an object-oriented database stores complex data and relationships between data directly, without mapping to relational rows and columns.
A data warehouse is a large collection of data that can be used to help an organisation make key business decisions.
Here’s a more precise definition of the term, as coined by Bill Inmon, (considered by many to be “the father of data warehousing”):
A data warehouse is a subject-oriented, integrated, nonvolatile, and time-variant collection of data in support of management’s decisions.
The term big data refers to the massive amounts of data – both structured and unstructured – that inundate organisations on a day-to-day basis.
Typically, big data is so large, and accumulates so fast, that traditional data storage and processing applications are inadequate.
The big data industry helps organisations capture and analyse their big data, so that those organisations can make more informed business decisions.