Database management involves the organization, storage, security, and retrieval processes of an organization’s data and database(s). Managing databases involves designing, implementing, and supporting stored data to unlock its value and deliver actionable business insights.
Database management has historically included performance monitoring and tuning, storage and capacity planning, backup and recovery, compliance, data archiving, partitioning, replication, and sunsetting—that is, any processes supporting an organization’s data analysis and business intelligence efforts.
Benefits of Database Management
Database management involves designing, implementing, and supporting stored data to derive valuable insights. It allows organizations to:
- Store multiple types of data from various sources
- Streamline operations and automate processes
- Ensure query performance
- Improve data consistency, quality, governance, security, and sharing
Database management versus data management
Database management involves the monitoring, administration, and maintenance of databases and database groups across an organization. On the other hand, data management involves the administrative and governance processes an organization employs to acquire, validate, store, protect, and process its data. While both database management and data management are meant to improve data access, accuracy, and timeliness for users, database management focuses on the overall systems and processes necessary to enable data management best practices.
Database Management Systems
A database management system (DBMS) functions as the foundational platform responsible for the creation and administration of databases within an organization. Typically, a DBMS processes an organization’s data, including the data’s format. It also defines rules to validate and standardize the data, whether structured or unstructured.
There are five types of database management systems, namely:
Relational, which contain multiple tables of data records and use SQL for interaction.
Hierarchical, with pre-defined relationships between data records.
Network, which is a kind of hierarchical database management system that allows for multiple relationships between data records
Object-oriented, in which information is represented as objects, allowing for different types of relationships between multiple objects.
NoSQL, or non-relational, which allow for large amounts of unstructured and semi-structured data.
Database Management Systems Versus Relational Database Management Systems
A relational database management system (RDBMS) is a type of database management system. The distinguishing characteristics of an RDBMS are its allowance for multiple tables of data records and the use of SQL for interaction.
Comparison of typical hierarchical DBMSs and RDBMSs
DBMS | RDBMS | |
Structure | Hierarchical | Tabular |
Distributed databases | Not supported | Supported |
Data capacity | Limited | Unlimited |
User capacity | One user at a time | Allows for multiple users simultaneously |
Database Management Systems Versus Traditional File Systems
Traditional file systems, such as those of a computer’s hard drive, organize small amounts of data but are limited in capacity and access. A database management system, on the other hand, allows for much larger data sets and better data integrity, security, sharing, and querying.
Snowflake Data Cloud
Companies previously used data warehouses and separate physical data marts to allow multiple stakeholders and data consumers to store and analyze enterprise applications. Now organizations commonly mix data processing technologies and analytics techniques, but this provides only limited insight from unique data slices.
Snowflake's Data Cloud platform offers highly scalable and fully elastic database management, allowing businesses to run critical data workloads in one location. Snowflake supports data warehousing, data lake, data sharing, data applications, AI/ML, and data engineering workloads on one platform.