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Understanding Database Management Concepts

What Is Database Management?

Database management is the process of collecting, storing, organizing, maintaining and analyzing data. Organizations leverage various database management practices and tools, for the purpose of driving data-based decisions and strategic planning. There is a wide range of solutions applicable for database management, of which database management systems (DBMSs) are the most common.



What is a Database Management System (DBMS)?

A DBMS enables organizations to effectively manage databases. DevOps and DataOps teams leverage DBMS technology to perform tasks such as creating and updating databases, as well as reading, writing, and deleting data. 


Functions of a DBMS

The main purpose of a DBMS is to provide an interface that enables organizations to standardize data management consistently across teams and departments. This is achieved through the management of three core aspects:

  • Data-which is aggregated, stored, and analyzed by the organization. 
  • Database engines-enables organizations to access, store, and modify data. 
  • Database schema-determines the logical structure for each database. 

When managed well, these core aspects can help organizations ensure data integrity, security, and concurrency throughout the entire data lifecycle.


A DBMS typically provides capabilities for the following tasks: 

  • Data management modifications 
  • Monitoring and tuning 
  • Data security 
  • Backup and recovery


Advanced capabilities of DBMS include:

  • Automation-for a wide variety of tasks, including logging and auditing, or rollbacks and restarts.
  • Centralization-unify data processes into one visualized workflow, accessed via multiple devices and locations, and enable different users to display different views of one database schema.
  • Access controls-determine roles and privileges for each user, to ensure users gain limited access to corporate data and prevent abuse of privileges. 
  • User friendly-DBMSs often provide an intuitive user experience, which enables users of different skill levels to access and leverage data.


Another huge advantage of DBMS is data independence. When the DBMS is designed for logical and physical data independence, users and developers do not need to perform modifications when the data is moved. A DBMS can handle this task, provided it is connected with an application programming interface (API) to any new data sources.


DBMS Concepts

DBMS solutions come equipped with a unique set of components, each responsible for performing different tasks. Here are the most basic DBMS components:

  • Software-A DBMS is a software-based system that provides a management interface, which helps users control databases and data sources.
  • Data-DBMS provides controls for managing operational data, such as records and metadata, as well as index files, data dictionaries, and administrative information. 
  • Procedures-documents that standardize database management, used as guidelines by employees and users, and as automation policies.  
  • Database languages-DBMS use various languages to perform tasks such as controlling user access and specifying database schema. DBMS languages include Data Manipulation Language (DML), Data Definition Language (DDL), Data Control Language (DCL), and Database Access Language (DAL).
  • Query processor-serves as a communication intermediary between users and the DBMS data engine. The query processor enables users to query requests, for example, by entering instructions in Structured Query Language (SQL).
  • Runtime database manager-enables DBMS to centralize management of runtime data. A runtime database manager validates user authorizations, processes approved queries, determines which strategy provides optimal query results, ensures data integrity, and handles any task that requires handling query and runtime data.
  • Database manager-handles database jobs and enables administrators to perform database operations and maintenance tasks, including data backup and restore, cloning, deleting, updating the database, and executing patches.   
  • Database engine-performs the main data storage and retrieval tasks. A database engine can be built into the DBMS software or as a remote resource accessed via an API. 
  • Report generator-enables users to extract DBMS files and display the information in structured formats, according to predefined specifications. Report generation processes help users perform analyses and derive actionable insights.


DBMS Categories and Technologies

There is a wide range of DBMS solutions, dedicated to different data types, sources, and use cases. Here are the most common types of DBMS categories and technologies:

  • RDBMS-a relational database management system (RDBMS) is designed specifically for relational databases, which store data in structured formats such as columns and rows. Popular RDBMS solutions include Oracle Database, MySQL, and Microsoft SQL Server.
  • Network DBMS-a database in which inter-record type relationships are organized using one-to-many sets. This differs from a Hierarchical Model in that it allows a record type to be a member of more than one set. Individual rows can be retrieved using API functions that allow an application to navigate through individual set instances. Raima Database is one of the known database vendors that have network capabilities.
  • NoSQL DBMS-a NoSQL database can store data that is “not only SQL”, in formats that are not only relational. Mainly, NoSQL databases enable you to store schemaless data, and this type of design requires different management capabilities. Popular NoSQL DBMS solutions include MongoDB, Amazon DynamoDB, Cassandra, and Azure Cosmos DB.
  • In-memory DBMS (IMDBMS)-also known as main memory DBMS, these systems leverage memory for data storage, ensuring fast access to data. IMDBMS, which uses fewer CPU instructions than disk-based systems, is typically used to improve performance, reducing I/O latency and processing overhead.
  • Multi-model DBMS-can support multiple types of data models. This type of data strategy is often supported by NoSQL solutions, which are often required to store different types of data together. 
  • NewSQL DBMS-designed like RDBMS platforms with functionalities that support NoSQL distribution. NewSQL DBMS often provide capabilities for managing high levels of data, such as ACID-compliance and real-time processing. Popular NewSQL DBMS include Google Cloud Spanner, MemSQL, Splice Machine, and ClustrixDB.


Database Management Concepts with Raima

RaimaDB is an RDBMS (Relational Database Management System) developed for IoT Edge use cases. By combining the network and relational model technologies in a single system, RaimaDB lets you organize and access information efficiently, regardless of the complexity of the data. The Raima database system is optimized to run as both an in-memory DBMS with the ability to persist data to disk or as a fully disk based database system.  It is highly performant with low I/O latency and minimal processing overhead. 

RaimaDB gives developers a rich set of database features, including multiple APIs and indexing methods requiring minimal resources. A great DBMS for embedded devices and applications running on real-time operating systems. 

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