The advent of the Internet led to exponential growth of the database industry. Average desktop users began to use client-server database systems to access computer systems that contained legacy data.
With the increased use of point-of-sale technology, online transaction processing and online analytic processing began to come of age. Although the Internet industry experienced a decline in the early s, database applications continue to grow. New interactive applications were developed for PDAs, point-of-sale transactions, and consolidation of vendors.
Today, databases are everywhere and are used to enhance our day-to-day life. From personal cloud storage to predicting the weather, many of the services we utilize today are possible due to databases.
Presently, there are many new players in the non-relational database space offering specific solutions. Searching for records could be accomplished by one of three techniques:. He wrote a series of papers, in , outlining novel ways to construct databases. His ideas eventually evolved into a paper titled A Relational Model of Data for Large Shared Data Banks , which described a new method for storing data and processing large databases.
RDBM Systems were an efficient way to store and process structured data. Unstructured data is both non-relational and schema-less, and relational database management systems simply were not designed to handle this kind of data. MySQL has evolved into an extremely scalable database system with the ability to operate on multiple platforms. Some key features of MySQL follow:. A DBMS using columns is quite different from traditional relational database systems.
It stores data as portions of columns, instead of as rows. The change in focus, from row to a column, lets column databases maximize their performance when large amounts of data are stored in a single column. This strength can be extended to data warehouses and CRM applications. A key-value pair database is useful for shopping cart data or storing user profiles.
All access to the database is done using a primary key. Typically, there is no fixed schema or data model. The key can be identified by using a random lump of data.
Key-value stores are not useful when there are complex relationships between data elements or when data needs to be queried by other than the primary key. Generally speaking, NoSQL databases are preferable in certain use cases to relational databases because of their speed and flexibility. This non-relational system is fast, uses an ad-hoc method of organizing data, and processes high volumes of different kinds of data. Each of these organizations stores and processes colossal amounts of unstructured data.
Unfortunately, NoSQL does come with some problems. It can also be difficult to find tech support if your open-source NoSQL system goes down. Hardware can fail, but NoSQL databases are designed with a distribution architecture that includes redundant backup storage of both data and function. It does this by using multiple nodes database servers.
If one, or more, of the nodes goes down, the other nodes can continue with normal operations and suffer no data loss. When used correctly, NoSQL databases can provide high performance at an extremely large scale, and never shut down. Particularly, it was the time of growth for the relational database model. Earlier navigational models faded, while the commercialisation of relational systems saw this type of database rise in use and popularity. The s also saw SQL become the standard language used for databases, which we still use today.
This concept appeared in the mids. The early days of object-oriented database management did not see the idea as a popular one. This was partially due to the costs and time it would take to rewrite existing databases to support the approach.
However, object oriented database systems grow more popular in the 90s. Another key event impacting the history of databases in the 90s was the creation of the World Wide Web. High investments in online businesses fuelled demand for client-server database systems.
As such, the internet helped to power exponential growth of the database industry in the s. A notable outcome of this was the creation of MySQL in , which was open source. This meant that it provided an alternative to the database systems offered by big companies like Oracle and Microsoft. MySQL is still used by many today. In , the term NoSQL not only structured query language was coined.
It refers to databases that use query language other than SQL to store and retrieve data. NoSQL databases are useful for unstructured data , and they saw a growth in the s.
This is a notable development in the history of databases because NoSQL allowed for faster processing of larger, more varied datasets. NoSQL databases are more flexible than the traditional relational databases that had risen the decade before. The s were a decade of increased data awareness, with the rise of big data and an increased emphasis on data protection. And these trends naturally inform the history of databases.
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