por Databases are recognized as a kind of repository of information through a structure defined and managed by a specific system for big data. Now, knowing the history of the origin of databases is just as important as learning how to manipulate them.
For this reason, throughout the post, we will explain the stages and development of the history of the origin of databases and its impact within the ecosystem of Big Data languages, systems and tools, until reaching the recent history of big data.
History of the origin of databases
If you have also wondered why databases were created, here is your answer:
A database has always been recognized as the grouping of certain information that has a certain interest or value to be stored. However, depending on a certain area, more specifications are made regarding their classification.
In sum, with the passage of time, Databases have gained more strength and impact for the development of multiple data analyses. Nowadays, with issues such as social networks and websites, it is essential to make effective use of them.
Now, to carry out a study In order to highlight the value of a database, it is necessary to know the history of the origin of databases. Next, we guide you with the main moments of its evolution.
Origin of databases
Have you wondered why databases arise?
At first, the structuring was based on supporting business applicationswhich is why relational algebra and basic database systems arise.
In a first approach, the databases used conventional methods related to traditional paper, folders and files.
This later led to the first computers and Databases began to be related mainly to the field of computing.
Industry raid
Time after, With technological advancement, relational database tools began to be developed and formed. that began to take a position in the market.
The introduction of object-oriented languages cemented this approach with tools such as ORM, SQLServer and MVC itself.
More industry development
On the other hand, industries began to get on the technological bandwagon and, clearly, Needs began to arise to incorporate and read data in different ways.
Furthermore, the science and research industry began to give fruit to other paradigms, such as Graph databases with tools like Neo4j and OrientDB.
The boom of Applications and Social Networks
Finally, the boom has come largely supported by the rise of applications and social networks. In addition to a greater amount of data, the enormous amounts of data requests with a More flexible structure began to be the rule in most projects.
On the other hand, from here non-relational databases emergewhich seek scalability and performance above fault tolerance and data accuracy.
How to continue learning about Big Data?
In the course of this post, we have briefly explained the history of the origin of databases with some examples. However, what we have shared with you is only a small part of everything they involve. databases within the world of Big Data.
For this reason, at we advise you to look at our Ful Stack Big Data, Artificial Intelligence & Machine Learning Bootcamp. Thanks to this bootcamp, you will be able to see and develop a complete painting of the process of ingesting, classifying, safeguarding, processing and presenting data using different tools. We will focus on architecture concepts such as availability, scalability, resilience and others. Don’t think twice and get started!