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Learn about SQL and NoSQL

Database, also called electronic database, any collection of data, or information, that is specially organized for rapid search and retrieval by a computer. Databases are structured to facilitate the storage, retrieval, modification, and deletion of data in conjunction with various data-processing operations. Learn database more and more;
DBMS stands for database management system; in other words, a system that manages databases. Examples of DBMSes are Oracle and SQL Server. These are systems that can be used to manage transactional databases, such as HR systems, banking systems and so on. These are typically optimized for performing transactions.
There are four structural types of database management systems:
  • Hierarchical databases.
  • Network databases.
  • Relational databases.
  • Object-oriented databases.
To make this information more useful, easy to access and protected we use database management systems. DBMS is important because it manages the data efficiently and allow users to perform multiple tasks on it with the ease. … And DBMS provides efficient ways to accomplish that task. Learn database for every sector of IT.
We discussed four main types of databases: text databases, desktop database programs, relational database management systems (RDMS), and NoSQL and object-oriented databases. We also talked about two ways to categorize databases based on their logical design: operational databases and database warehouses. Let’s learn database more.
One of the most fundamental choices to make when developing an application is whether to use a SQL or NoSQL database to store the data. Conventional SQL (i.e. relational) databases are the product of decades of technology evolution, good practice, and real-world stress testing. They are designed for reliable transactions and ad hoc queries, the staples of line of business applications. But they also come burdened with restrictions—such as rigid schema—that make them less suitable for other kinds of apps.
NoSQL databases arose in response to those limitations. NoSQL systems store and manage data in ways that allow for high operational speed and great flexibility on the part of the developers. Many were developed by companies like Google, Amazon, Yahoo, and Facebook that sought better ways to store content or process data for massive websites. Unlike SQL databases, many NoSQL databases can be scaled horizontally across hundreds or thousands of servers.
What is SQL?
SQL is used to communicate with a database. According to ANSI (American National Standards Institute), it is the standard language for relational database management systems. SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database.
Top 5 Best Databases
  1. MySQL. MySQL is used in almost all the open source web projects that require a database in the back-end.
  2. PostgreSQL. PotgreSQL is a open source object-relational database system.
  3. Oracle. Oracle is the best database for any mission critical commercial application.
  4. SQLite.
  5. Microsoft SQL Server.
What is NoSQL?
NoSQL stands for Not Only SQL, some thinks that it’s non SQL. NoSQL is an approach to databases that represents a shift away from traditional relational database management systems (RDBMS). … Relational databases rely on tables, columns, rows, or schemas to organize and retrieve data. In contrast, NoSQL databases do not rely on these structures and use more flexible data models.
A traditional database product would prefer more predictable, structured data. A relational database may require vertical and, sometimes horizontal expansion of servers, to expand as data or processing requirements grow. … NoSQL is a whole new way of thinking about a database. NoSQL is not a relational database. Let’s learn databse more…

NoSQL vs SQL

High-Level Differences: SQL databases are primarily called as Relational Databases (RDBMS): whereas NoSQL database are primarily called as non-relational or distributed database. SQL databases have predefined schema whereas NoSQL databases have dynamic schema for unstructured data.
The fundamental difference between SQL and NoSQL is not all that complicated. Each has a different philosophy for how data should be stored and retrieved.
With SQL databases, all data has an inherent structure. A conventional database like Microsoft SQL Server, MySQL, or Oracle Database uses a schema—a formal definition of how data inserted into the database will be composed. For instance, a given column in a table may be restricted to integers only. As a result, the data recorded in the column will have a high degree of normalization. A SQL database’s rigid schema also makes it relatively easy to perform aggregations on the data, for instance by way of JOINs. Let’s learn database more on following:
With NoSQL, data can be stored in a schema-less or free-form fashion. Any data can be stored in any record. Among the NoSQL databases, you will find four common models for storing data, which lead to four common types of NoSQL systems:
  1. Document databases (e.g. CouchDB, MongoDB). Inserted data is stored in the form of free-form JSON structures or “documents,” where the data could be anything from integers to strings to freeform text. There is no inherent need to specify what fields, if any, a document will contain.
  2. Key-value stores (e.g. Redis, Riak). Free-form values—from simple integers or strings to complex JSON documents—are accessed in the database by way of keys.
  3. Wide column stores (e.g. HBase, Cassandra). Data is stored in columns instead of rows as in a conventional SQL system. Any number of columns (and therefore many different types of data) can be grouped or aggregated as needed for queries or data views.
  4. Graph databases (e.g. Neo4j). Data is represented as a network or graph of entities and their relationships, with each node in the graph a free-form chunk of data.
Schema-less data storage is useful in the following scenarios:
  1. You want fast access to the data, and you’re more concerned with speed and simplicity of access than reliable transactions or consistency.
  2. You’re storing a large volume of data, and you don’t want to lock yourself into a schema, as changing the schema later could be slow and painful.
  3. You’re taking in unstructured data from one or more sources that produce it, and you want to keep the data in its original form for maximum flexibility.
  4. You want to store data in a hierarchical structure, but you want those hierarchies to be described by the data itself, not an external schema. NoSQL allows data to be casually self-referential in ways that are more complex for SQL databases to emulate.
Hope all have understood the differences between SQL and NoSQL. We will learn more about Database SQL and NoSQL in the programming tutorials… Keep learning database, Never stop learning programming, Never stop developing your skill…

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