Database (computing)

Database (computing)
Name	Database (computing)
Type	System software

Database (computing) A database in computing is a structured collection of persistent data managed by a database management system and accessed by applications, services, and users. Databases underpin systems ranging from enterprise resource planning to mobile applications and scientific computing, linking to platforms and organizations that include IBM, Oracle Corporation, Microsoft, Amazon Web Services, and Google.

Definition and Purpose

A database stores, organizes, and retrieves information to support operations, analytics, and decision-making across systems like SAP SE, Salesforce, Walmart, Netflix, and NASA. It provides durable storage for data produced by Linux, Windows Server, Android, iOS, and middleware such as Apache HTTP Server and Nginx, enabling interoperability with frameworks like Spring Framework, Django, Ruby on Rails, Node.js, and React. Databases enable reporting, business intelligence, and machine learning workflows used by institutions such as Harvard University, Stanford University, MIT, CERN, and NASA.

Data Models and Database Types

Data models define data representation: relational models pioneered by IBM Research and theorists like E. F. Codd; document models implemented by vendors such as MongoDB, Inc. and projects like Apache CouchDB; key–value stores exemplified by Redis and Amazon DynamoDB; wide-column stores represented by Apache Cassandra and HBase; and graph databases like Neo4j and research systems from Facebook and Twitter. Hybrid and multimodel systems combine paradigms in products from Oracle Corporation, Microsoft Azure Cosmos DB, and ArangoDB. Specialized time-series and geospatial databases appear in tools from InfluxData, Esri, and PostGIS.

Architecture and Components

A database architecture comprises storage engines, query processors, transaction managers, and metadata catalogs used by enterprises such as Goldman Sachs, JPMorgan Chase, Citigroup, HSBC, and Deutsche Bank. Components include data files managed on filesystems like ext4, NTFS, and ZFS; buffer pools and caches influenced by designs from Intel and AMD; and networking supported by Cisco Systems and Juniper Networks. High-availability architectures use replication and clustering technologies from Red Hat, Canonical, VMware, and cloud providers Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

Querying and Transaction Management

Query languages such as SQL standardize relational access in products from Oracle Corporation, IBM Db2, and Microsoft SQL Server, while APIs like ODBC and JDBC enable connectivity used by SAP SE, Tableau Software, and Qlik. NoSQL systems expose RESTful and binary protocols adopted by Twitter, LinkedIn, Uber, and Airbnb. Transaction management relies on ACID principles advanced by academic work at University of California, Berkeley and University of Washington and on consensus algorithms such as Paxos and Raft employed by systems from Google and HashiCorp. Concurrency control techniques derive from research at institutions like MIT and Stanford University and are implemented in commercial products from Microsoft and Oracle Corporation.

Design, Modeling, and Normalization

Schema design and data modeling use techniques from computer science curricula at Carnegie Mellon University and Princeton University and tools from vendors such as Erwin, IBM Rational, and Sparx Systems. Normalization theory traces to E. F. Codd and is balanced against denormalization strategies used by Amazon, Netflix, and Facebook to optimize read performance. Entity–relationship modeling and UML practices are common in enterprises like Siemens and General Electric, while domain-driven design is employed by software teams at ThoughtWorks and Atlassian.

Security, Integrity, and Backup

Database security includes authentication, authorization, auditing, and encryption implemented by vendors such as Symantec, McAfee, Palo Alto Networks, and Fortinet. Data integrity mechanisms use checksums and transactional guarantees applied in compliance with regulations like General Data Protection Regulation and standards from organizations such as ISO and NIST. Backup and disaster recovery strategies are provided by solutions from Veeam, Commvault, and cloud services by Amazon Web Services, Microsoft Azure, and Google Cloud Platform and are applied in sectors including Healthcare and Financial services overseen by regulators like the Securities and Exchange Commission.

Performance, Scalability, and Deployment

Performance tuning leverages indexing, caching, and partitioning techniques used in systems deployed by Facebook, Twitter, YouTube, and Instagram. Scalability strategies include sharding used by Google and Amazon, horizontal scaling in container orchestrations via Kubernetes and Docker, and edge deployments supported by CDNs such as Cloudflare and Akamai Technologies. Deployment models span on-premises datacenters operated by Equinix and Digital Realty, private clouds maintained by VMware, and managed database services from Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

Category:Computer data storage