Database

A database is an organized collection of structured information, or data, typically stored electronically in a computer system. A database is usually controlled by a?database management system (DBMS). Together, the data and the DBMS, along with the applications that are associated with them, are referred to as a database system, often shortened to just database.

Data within the most common types of databases in operation today is typically modeled in rows and columns in a series of tables to make processing and data querying efficient. The data can then be easily accessed, managed, modified, updated, controlled, and organized. Most databases use structured query language (SQL) for writing and querying data.

What’s the difference between a database and a spreadsheet?

Databases and spreadsheets (such as Microsoft Excel) are both convenient ways to store information. The primary differences between the two are:

• How the data is stored and manipulated
• Who can access the data
• How much data can be stored

Spreadsheets were originally designed for one user, and their characteristics reflect that. They’re great for a single user or small number of users who don’t need to do a lot of incredibly complicated data manipulation. Databases, on the other hand, are designed to hold much larger collections of organized information—massive amounts, sometimes. Databases allow multiple users at the same time to quickly and securely access and query the data using highly complex logic and language.

Types of databases

There are many different types of databases. The best database for a specific organization depends on how the organization intends to use the data.

Relational databases

• Relational databases?became dominant in the 1980s. Items in a relational database are organized as a set of tables with columns and rows. Relational database technology provides the most efficient and flexible way to access structured information.

Object-oriented databases

• Information in an object-oriented database is represented in the form of objects, as in object-oriented programming.

Distributed databases

• A distributed database consists of two or more files located in different sites. The database may be stored on multiple computers, located in the same physical location, or scattered over different networks.

Data warehouses

• A central repository for data, a data warehouse is a type of database specifically designed for fast query and analysis.

NoSQL databases

• A?NoSQL, or nonrelational database, allows unstructured and semistructured data to be stored and manipulated (in contrast to a relational database, which defines how all data inserted into the database must be composed). NoSQL databases grew popular as web applications became more common and more complex.

Graph databases

• A graph database stores data in terms of entities and the relationships between entities.
• OLTP databases.?An OLTP database is a speedy, analytic database designed for large numbers of transactions performed by multiple users.

These are only a few of the several dozen types of databases in use today. Other, less common databases are tailored to very specific scientific, financial, or other functions. In addition to the different database types, changes in technology development approaches and dramatic advances such as the cloud and automation are propelling databases in entirely new directions. Some of the latest databases include

Open source databases

• An open source database system is one whose source code is open source; such databases could be SQL or NoSQL databases.

Cloud databases

• A?cloud database?is a collection of data, either structured or unstructured, that resides on a private, public, or hybrid cloud computing platform. There are two types of cloud database models: traditional and database as a service (DBaaS). With DBaaS, administrative tasks and maintenance are performed by a service provider.

Multimodel database

• Multimodel databases combine different types of database models into a single, integrated back end. This means they can accommodate various data types.

Document/JSON database

• Designed for storing, retrieving, and managing document-oriented information,?document databases?are a modern way to store data in JSON format rather than rows and columns.

Self-driving databases

• The newest and most groundbreaking type of database, self-driving databases (also known as autonomous databases) are cloud-based and use machine learning to automate database tuning, security, backups, updates, and other routine management tasks traditionally performed by database administrators.

Database challenges

Today’s large enterprise databases often support very complex queries and are expected to deliver nearly instant responses to those queries. As a result, database administrators are constantly called upon to employ a wide variety of methods to help improve performance. Some common challenges that they face include:

• Absorbing significant increases in data volume.?The explosion of data coming in from sensors, connected machines, and dozens of other sources keeps database administrators scrambling to manage and organize their companies’ data efficiently.
• Ensuring data security.?Data breaches are happening everywhere these days, and hackers are getting more inventive. It’s more important than ever to ensure that data is secure but also easily accessible to users.
• Keeping up with demand.?In today’s fast-moving business environment, companies need real-time access to their data to support timely decision-making and to take advantage of new opportunities.
• Managing and maintaining the database and infrastructure.?Database administrators must continually watch the database for problems and perform preventative maintenance, as well as apply software upgrades and patches. As databases become more complex and data volumes grow, companies are faced with the expense of hiring additional talent to monitor and tune their databases.
• Removing limits on scalability.?A business needs to grow if it’s going to survive, and its data management must grow along with it. But it’s very difficult for database administrators to predict how much capacity the company will need, particularly with on-premises databases.
• Ensuring data residency, data sovereignty, or latency requirements.?Some organizations have use cases that are better suited to run on-premises. In those cases, engineered systems that are pre-configured and pre-optimized for running the database are ideal. Customers achieve higher availability, greater performance and up to 40% lower cost with Oracle Exadata, according to?Wikibon’s recent analysis (PDF).