Any activity that people undertake on the internet, whether it is for recreation, entertainment, or business leads to data generation. All business processes from finance and accounts to human relations to materials management, manufacturing, and sales and distribution generates data. Similarly, when you are running a digital content management system or recording any transactional information, it results in data generation. Since data contains information that is vital for recording the history of business, aids decision making, and helps to understand the process performance, it is necessary to store data in databases for future use. Therefore, it is only natural that every digital application makes use of databases.
Databases have been in use since the early days of computer applications, and depending on the requirements of collecting and disseminating data, the primary choice is between centralized databases and distributed databases. Although databases have evolved through the years, the broad classification still holds good.
Centralized databases are centralized systems that store data gathered from multiple data sources and applications stored at a single place. The applications depend on some authentication processes that allow users to access data safely and securely. The Central Library in a college or university that acts as a central database for all other libraries of the college or university is an example of a centralized database.
It is easier to manage data in a centralized database without affecting the core data while maintaining data consistency. Centralized databases provide better data quality, but maintaining the database is costly because it requires the services of database administrators of RemoteDBA.com to manage the database efficiently. However, centralized databases have slower speeds due to their large size, and updating the system is not easy.
As the name implies, data remains distributed within several databases in the system that stay connected via communication links. Distributed databases may be homogenous databases if it uses the same application process and hardware and even the same operating system. Heterogenous distributed databases make use of different operating systems and hardware and different application procedures.
Distributed databases allow modular development, which is an advantage, and a single server failure will not affect the entire database.
We will now discuss the types of databases from the application perspective. Depending on the data type and structure, data model, and the manner of use of data, there are two types of databases that you can consider – relational databases and non-relational databases. During database selection, you must also consider the querying mechanism or schema required, latency and consistency requirements as well as transactional speed.
Relational database management systems (RDBMS) / SQL
RDBMS is the most widely used database system as compared to NoSQL database systems. Relational databases that were introduced during the 1970s store data in a way so that it can be displayed in the form of a table containing columns and rows. It appears like a collection of tables with each table having a schema that represents the data types and fixed attributes that the items in the table will have. The database systems have the functionalities for creating, reading, updating, and deleting data with the help of SQL or Structured Query Language statements.
Relational databases have tables that store only key-value pairs and providekeys associated with it that are useful for identifying specific rows or columns of a table for faster access to any specific table, column, or row of interest. To address the concerns about data integrity in relational databases, RDBMS uses several constraints to ensure the reliability and accuracy of the data contained in the table.
Oracle, My SQL, Microsoft SQL Server, PostgreSQL, and DB2 are some of the most popular relational database systems.
Advantages of RDBMS
Relational databases are mature technologies, well documented, and several established corporations sell and maintain it. A large pool of qualified developers has experience in RDBMS and SQL, and the systems satisfy the requirements of Atomicity, Consistency, Isolation, and Durability (ACID).
Disadvantages of RDBMS
The schema type of RDBMS does not work at all with unstructured and semi-structured data and unsuitable for IoT event loads and extensive analytics. One-to-one mapping of the tables with a class or object representing the same data is not possible. Complex data sets or data with variable-length records are not easy to handle in RDBMS.
Non-relational databases / NoSQL
As web applications became more complex, NoSQL databases started gaining popularity as an alternative to relational databases. The most glaring difference between NoSQL and RDBMS is that the schemas of RDBMS rigidly define how to type and compose data for inserting it in the database. Still, NoSQL databases are flexible and allow storing and manipulation of unstructured data as well as semi-structured data.
Types of NoSQL databases
There are many types of NoSQL databases, but some can be a hybrid type and belong to more than one category. A typical example is the Couchbase, which is a hybrid of a document database and key-value store.
Key-value stores – Databases like the Amazon Dynamo DB and Redis are simple DBMS that store key-value pairs only and provide the basic functionality for retrieving the value attached to a known key. These databases suit the embedded databases due to the simplicity of the key-value stores because the data is simple, and operations are speedy.
Wide Column Stores – HBase, Scylla and Cassandra are systems that are independent of schema that enables users to store data in tables or column families, a single row that represents a record which is a multi-dimensional key-value store. These databases are highly scalable for managing petabytes of data across thousands of commodity servers in a massively distributed system.
Document Stores – Couchbase and Mongo DB are schema-less systems capable of storing data as JSON documents. Document stores are like Wide Column Stores and Key-value Stores, but the document name is the key, and the contents of the document are the value.
Graph databases – Graph databases like Datastax Enterprise Graph and Neo4J represent data in the form of a network of related objects or nodes to visualize data and graph analytics. Free form data contained in a node or object is connected by relationships and grouped according to the labels.
The way you want to utilize the database will influence your choice.
Author bio –
Kristen Smith is a web developer and experienced professional in database management and administration. She says you must deploy credible companies like database administrators of RemoteDBA.com to help you maintain and secure any database system with success!