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In computing , a database is an organized collection of data or a type of data store based on the use of a database management system ( DBMS ), the software that interacts with end users , applications , and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system . Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database.

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69-514: RedLightGreen was a database of bibliographic descriptions on the Web created by Research Libraries Group (RLG) . It used a set of four million records extracted from OCLC 's WorldCat database, and was designed to help novice users make selections from the vast bibliographic resources they would encounter in such a large set. RedLightGreen also allowed users to create citations for works found. Work on RedLightGreen began in 2001 with funding from

138-1107: A computer monitor or input device, audio hardware and USB interfaces. Many servers do not have a graphical user interface (GUI). They are configured and managed remotely. Remote management can be conducted via various methods including Microsoft Management Console (MMC), PowerShell , SSH and browser-based out-of-band management systems such as Dell's iDRAC or HP's iLo . Large traditional single servers would need to be run for long periods without interruption. Availability would have to be very high, making hardware reliability and durability extremely important. Mission-critical enterprise servers would be very fault tolerant and use specialized hardware with low failure rates in order to maximize uptime . Uninterruptible power supplies might be incorporated to guard against power failure. Servers typically include hardware redundancy such as dual power supplies , RAID disk systems, and ECC memory , along with extensive pre-boot memory testing and verification. Critical components might be hot swappable , allowing technicians to replace them on

207-432: A data modeling construct for the relational model, and the difference between the two has become irrelevant. The 1980s ushered in the age of desktop computing . The new computers empowered their users with spreadsheets like Lotus 1-2-3 and database software like dBASE . The dBASE product was lightweight and easy for any computer user to understand out of the box. C. Wayne Ratliff , the creator of dBASE, stated: "dBASE

276-484: A 1962 report by the System Development Corporation of California as the first to use the term "data-base" in a specific technical sense. As computers grew in speed and capability, a number of general-purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial use. Interest in a standard began to grow, and Charles Bachman , author of one such product,

345-452: A client. A single server can serve multiple clients, and a single client can use multiple servers. A client process may run on the same device or may connect over a network to a server on a different device. Typical servers are database servers , file servers , mail servers , print servers , web servers , game servers , and application servers . Client–server systems are usually most frequently implemented by (and often identified with)

414-403: A computer program that turns a computer into a server, e.g. Windows service . Originally used as "servers serve users" (and "users use servers"), in the sense of "obey", today one often says that "servers serve data", in the same sense as "give". For instance, web servers "serve [up] web pages to users" or "service their requests". The server is part of the client–server model ; in this model,

483-440: A custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions. Since DBMSs comprise a significant market , computer and storage vendors often take into account DBMS requirements in their own development plans. Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML ),

552-443: A database management system. Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups: Both a database and its DBMS conform to the principles of a particular database model . "Database system" refers collectively to the database model, database management system, and database. Physically, database servers are dedicated computers that hold

621-404: A database. One way to classify databases involves the type of their contents, for example: bibliographic , document-text, statistical, or multimedia objects. Another way is by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists

690-415: A device used for (or a device dedicated to) running one or several server programs. On a network, such a device is called a host . In addition to server , the words serve and service (as verb and as noun respectively) are frequently used, though servicer and servant are not. The word service (noun) may refer to the abstract form of functionality, e.g. Web service . Alternatively, it may refer to

759-543: A different chain, based on IBM's papers on System R. Though Oracle V1 implementations were completed in 1978, it was not until Oracle Version 2 when Ellison beat IBM to market in 1979. Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is now known as PostgreSQL . PostgreSQL is often used for global mission-critical applications (the .org and .info domain name registries use it as their primary data store , as do many large companies and financial institutions). In Sweden, Codd's paper

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828-463: A different type of entity . Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systems dominated in all large-scale data processing applications, and as of 2018 they remain dominant: IBM Db2 , Oracle , MySQL , and Microsoft SQL Server are the most searched DBMS . The dominant database language, standardized SQL for

897-423: A few of the adjectives used to characterize different kinds of databases. Connolly and Begg define database management system (DBMS) as a "software system that enables users to define, create, maintain and control access to the database." Examples of DBMS's include MySQL , MariaDB , PostgreSQL , Microsoft SQL Server , Oracle Database , and Microsoft Access . The DBMS acronym is sometimes extended to indicate

966-411: A server serves data for clients . The nature of communication between a client and server is request and response . This is in contrast with peer-to-peer model in which the relationship is on-demand reciprocation. In principle, any computerized process that can be used or called by another process (particularly remotely, particularly to share a resource) is a server, and the calling process or processes

1035-423: A service for the requester, which often runs on a computer other than the one on which the server runs. The average utilization of a server in the early 2000s was 5 to 15%, but with the adoption of virtualization this figure started to increase to reduce the number of servers needed. Strictly speaking, the term server refers to a computer program or process (running program). Through metonymy , it refers to

1104-449: A set of operations based on the mathematical system of relational calculus (from which the model takes its name). Splitting the data into a set of normalized tables (or relations ) aimed to ensure that each "fact" was only stored once, thus simplifying update operations. Virtual tables called views could present the data in different ways for different users, but views could not be directly updated. Codd used mathematical terms to define

1173-447: A single large "chunk". Subsequent multi-user versions were tested by customers in 1978 and 1979, by which time a standardized query language – SQL – had been added. Codd's ideas were establishing themselves as both workable and superior to CODASYL, pushing IBM to develop a true production version of System R, known as SQL/DS , and, later, Database 2 ( IBM Db2 ). Larry Ellison 's Oracle Database (or more simply, Oracle ) started from

1242-452: A strong demand for massively distributed databases with high partition tolerance, but according to the CAP theorem , it is impossible for a distributed system to simultaneously provide consistency , availability, and partition tolerance guarantees. A distributed system can satisfy any two of these guarantees at the same time, but not all three. For that reason, many NoSQL databases are using what

1311-454: A time by navigating the links, they would use a declarative query language that expressed what data was required, rather than the access path by which it should be found. Finding an efficient access path to the data became the responsibility of the database management system, rather than the application programmer. This process, called query optimization, depended on the fact that queries were expressed in terms of mathematical logic. Codd's paper

1380-717: Is a stub . You can help Misplaced Pages by expanding it . This article relating to library science or information science is a stub . You can help Misplaced Pages by expanding it . Database Small databases can be stored on a file system , while large databases are hosted on computer clusters or cloud storage . The design of databases spans formal techniques and practical considerations, including data modeling , efficient data representation and storage, query languages , security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance . Computer scientists may classify database management systems according to

1449-406: Is a client. Thus any general-purpose computer connected to a network can host servers. For example, if files on a device are shared by some process, that process is a file server . Similarly, web server software can run on any capable computer, and so a laptop or a personal computer can host a web server. While request–response is the most common client-server design, there are others, such as

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1518-618: Is a collaborative effort, Open Compute Project around this concept. A class of small specialist servers called network appliances are generally at the low end of the scale, often being smaller than common desktop computers. A mobile server has a portable form factor, e.g. a laptop . In contrast to large data centers or rack servers, the mobile server is designed for on-the-road or ad hoc deployment into emergency, disaster or temporary environments where traditional servers are not feasible due to their power requirements, size, and deployment time. The main beneficiaries of so-called "server on

1587-427: Is also less of a concern, but power consumption and heat output can be a serious issue. Server rooms are equipped with air conditioning devices. A server farm or server cluster is a collection of computer servers maintained by an organization to supply server functionality far beyond the capability of a single device. Modern data centers are now often built of very large clusters of much simpler servers, and there

1656-960: Is called eventual consistency to provide both availability and partition tolerance guarantees with a reduced level of data consistency. NewSQL is a class of modern relational databases that aims to provide the same scalable performance of NoSQL systems for online transaction processing (read-write) workloads while still using SQL and maintaining the ACID guarantees of a traditional database system. Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see Enterprise software ). Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples include computerized library systems, flight reservation systems , computerized parts inventory systems , and many content management systems that store websites as collections of webpages in

1725-515: Is classified by IBM as a hierarchical database . IDMS and Cincom Systems ' TOTAL databases are classified as network databases. IMS remains in use as of 2014 . Edgar F. Codd worked at IBM in San Jose, California , in one of their offshoot offices that were primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the CODASYL approach, notably

1794-405: Is contrasted with "user", distinguishing two types of host : "server-host" and "user-host". The use of "serving" also dates to early documents, such as RFC 4, contrasting "serving-host" with "using-host". The Jargon File defines server in the common sense of a process performing service for requests, usually remote, with the 1981 version reading: SERVER n. A kind of DAEMON which performs

1863-462: Is organized. Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it. Outside the world of professional information technology , the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index) as size and usage requirements typically necessitate use of

1932-421: Is still pursued in certain applications by some companies like Netezza and Oracle ( Exadata ). IBM started working on a prototype system loosely based on Codd's concepts as System R in the early 1970s. The first version was ready in 1974/5, and work then started on multi-table systems in which the data could be split so that all of the data for a record (some of which is optional) did not have to be stored in

2001-404: Is the basis of query optimization. There is no loss of expressiveness compared with the hierarchic or network models, though the connections between tables are no longer so explicit. In the hierarchic and network models, records were allowed to have a complex internal structure. For example, the salary history of an employee might be represented as a "repeating group" within the employee record. In

2070-602: The Andrew W. Mellon Foundation . It was one of the earliest experiments with the Functional Requirements for Bibliographic Records which provides a structured view of bibliographic data. On 1 July 2006, RLG was merged with OCLC , and it was announced that the RedLightGreen service would be replaced by WorldCat , via Open WorldCat, available at WorldCat.org. This World Wide Web –related article

2139-667: The Integrated Data Store (IDS), founded the Database Task Group within CODASYL , the group responsible for the creation and standardization of COBOL . In 1971, the Database Task Group delivered their standard, which generally became known as the CODASYL approach , and soon a number of commercial products based on this approach entered the market. The CODASYL approach offered applications

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2208-704: The Internet is based upon a client–server model. High-level root nameservers , DNS , and routers direct the traffic on the internet. There are millions of servers connected to the Internet, running continuously throughout the world and virtually every action taken by an ordinary Internet user requires one or more interactions with one or more servers. There are exceptions that do not use dedicated servers; for example, peer-to-peer file sharing and some implementations of telephony (e.g. pre-Microsoft Skype ). Hardware requirement for servers vary widely, depending on

2277-599: The Michigan Terminal System . The system remained in production until 1998. In the 1970s and 1980s, attempts were made to build database systems with integrated hardware and software. The underlying philosophy was that such integration would provide higher performance at a lower cost. Examples were IBM System/38 , the early offering of Teradata , and the Britton Lee, Inc. database machine. Another approach to hardware support for database management

2346-434: The database models that they support. Relational databases became dominant in the 1980s. These model data as rows and columns in a series of tables , and the vast majority use SQL for writing and querying data. In the 2000s, non-relational databases became popular, collectively referred to as NoSQL , because they use different query languages . Formally, a "database" refers to a set of related data accessed through

2415-471: The hierarchical model and the CODASYL model ( network model ). These were characterized by the use of pointers (often physical disk addresses) to follow relationships from one record to another. The relational model , first proposed in 1970 by Edgar F. Codd , departed from this tradition by insisting that applications should search for data by content, rather than by following links. The relational model employs sets of ledger-style tables, each used for

2484-409: The publish–subscribe pattern . In the publish-subscribe pattern, clients register with a pub-sub server, subscribing to specified types of messages; this initial registration may be done by request-response. Thereafter, the pub-sub server forwards matching messages to the clients without any further requests: the server pushes messages to the client, rather than the client pulling messages from

2553-514: The request–response model: a client sends a request to the server, which performs some action and sends a response back to the client, typically with a result or acknowledgment. Designating a computer as "server-class hardware" implies that it is specialized for running servers on it. This often implies that it is more powerful and reliable than standard personal computers , but alternatively, large computing clusters may be composed of many relatively simple, replaceable server components. The use of

2622-622: The 1980s and early 1990s. The 1990s, along with a rise in object-oriented programming , saw a growth in how data in various databases were handled. Programmers and designers began to treat the data in their databases as objects . That is to say that if a person's data were in a database, that person's attributes, such as their address, phone number, and age, were now considered to belong to that person instead of being extraneous data. This allows for relations between data to be related to objects and their attributes and not to individual fields. The term " object–relational impedance mismatch " described

2691-847: The Internet, the dominant operating systems among servers are UNIX-like open-source distributions , such as those based on Linux and FreeBSD , with Windows Server also having a significant share. Proprietary operating systems such as z/OS and macOS Server are also deployed, but in much smaller numbers. Servers that run Linux are commonly used as Webservers or Databanks. Windows Servers are used for Networks that are made out of Windows Clients. Specialist server-oriented operating systems have traditionally had features such as: In practice, today many desktop and server operating systems share similar code bases , differing mostly in configuration. In 2010, data centers (servers, cooling, and other electrical infrastructure) were responsible for 1.1–1.5% of electrical energy consumption worldwide and 1.7–2.2% in

2760-599: The United States. One estimate is that total energy consumption for information and communications technology saves more than 5 times its carbon footprint in the rest of the economy by increasing efficiency. Global energy consumption is increasing due to the increasing demand of data and bandwidth. Natural Resources Defense Council (NRDC) states that data centers used 91 billion kilowatt hours (kWh) electrical energy in 2013 which accounts to 3% of global electricity usage. Environmental groups have placed focus on

2829-686: The University of Michigan began development of the MICRO Information Management System based on D.L. Childs ' Set-Theoretic Data model. MICRO was used to manage very large data sets by the US Department of Labor , the U.S. Environmental Protection Agency , and researchers from the University of Alberta , the University of Michigan , and Wayne State University . It ran on IBM mainframe computers using

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2898-539: The ability to navigate around a linked data set which was formed into a large network. Applications could find records by one of three methods: Later systems added B-trees to provide alternate access paths. Many CODASYL databases also added a declarative query language for end users (as distinct from the navigational API ). However, CODASYL databases were complex and required significant training and effort to produce useful applications. IBM also had its own DBMS in 1966, known as Information Management System (IMS). IMS

2967-438: The actual databases and run only the DBMS and related software. Database servers are usually multiprocessor computers, with generous memory and RAID disk arrays used for stable storage. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large-volume transaction processing environments . DBMSs are found at the heart of most database applications . DBMSs may be built around

3036-456: The following functions and services a fully-fledged general purpose DBMS should provide: Server (computing) A server is a computer that provides information to other computers called " clients " on a computer network . This architecture is called the client–server model . Servers can provide various functionalities, often called "services", such as sharing data or resources among multiple clients or performing computations for

3105-411: The go" technology include network managers, software or database developers, training centers, military personnel, law enforcement, forensics, emergency relief groups, and service organizations. To facilitate portability, features such as the keyboard , display , battery ( uninterruptible power supply , to provide power redundancy in case of failure), and mouse are all integrated into the chassis. On

3174-400: The inconvenience of translating between programmed objects and database tables. Object databases and object–relational databases attempt to solve this problem by providing an object-oriented language (sometimes as extensions to SQL) that programmers can use as alternative to purely relational SQL. On the programming side, libraries known as object–relational mappings (ORMs) attempt to solve

3243-430: The lack of a "search" facility. In 1970, he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking A Relational Model of Data for Large Shared Data Banks . In this paper, he described a new system for storing and working with large databases. Instead of records being stored in some sort of linked list of free-form records as in CODASYL, Codd's idea

3312-576: The model: relations, tuples, and domains rather than tables, rows, and columns. The terminology that is now familiar came from early implementations. Codd would later criticize the tendency for practical implementations to depart from the mathematical foundations on which the model was based. The use of primary keys (user-oriented identifiers) to represent cross-table relationships, rather than disk addresses, had two primary motivations. From an engineering perspective, it enabled tables to be relocated and resized without expensive database reorganization. But Codd

3381-480: The relational approach, the data would be normalized into a user table, an address table and a phone number table (for instance). Records would be created in these optional tables only if the address or phone numbers were actually provided. As well as identifying rows/records using logical identifiers rather than disk addresses, Codd changed the way in which applications assembled data from multiple records. Rather than requiring applications to gather data one record at

3450-599: The relational model, has influenced database languages for other data models. Object databases were developed in the 1980s to overcome the inconvenience of object–relational impedance mismatch , which led to the coining of the term "post-relational" and also the development of hybrid object–relational databases . The next generation of post-relational databases in the late 2000s became known as NoSQL databases, introducing fast key–value stores and document-oriented databases . A competing "next generation" known as NewSQL databases attempted new implementations that retained

3519-419: The relational model, the process of normalization led to such internal structures being replaced by data held in multiple tables, connected only by logical keys. For instance, a common use of a database system is to track information about users, their name, login information, various addresses and phone numbers. In the navigational approach, all of this data would be placed in a single variable-length record. In

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3588-455: The relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs. The introduction of the term database coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily batch processing . The Oxford English Dictionary cites

3657-564: The running server without shutting it down, and to guard against overheating, servers might have more powerful fans or use water cooling . They will often be able to be configured, powered up and down, or rebooted remotely, using out-of-band management , typically based on IPMI . Server casings are usually flat and wide , and designed to be rack-mounted, either on 19-inch racks or on Open Racks . These types of servers are often housed in dedicated data centers . These will normally have very stable power and Internet and increased security. Noise

3726-623: The same problem. XML databases are a type of structured document-oriented database that allows querying based on XML document attributes. XML databases are mostly used in applications where the data is conveniently viewed as a collection of documents, with a structure that can vary from the very flexible to the highly rigid: examples include scientific articles, patents, tax filings, and personnel records. NoSQL databases are often very fast, do not require fixed table schemas, avoid join operations by storing denormalized data, and are designed to scale horizontally . In recent years, there has been

3795-411: The server as in request-response. The role of a server is to share data as well as to share resources and distribute work. A server computer can serve its own computer programs as well; depending on the scenario, this could be part of a quid pro quo transaction, or simply a technical possibility. The following table shows several scenarios in which a server is used. Almost the entire structure of

3864-412: The server's purpose and its software. Servers often are more powerful and expensive than the clients that connect to them. The name server is used both for the hardware and software pieces. For the hardware servers, it is usually limited to mean the high-end machines although software servers can run on a variety of hardwares. Since servers are usually accessed over a network, many run unattended without

3933-582: The technology progress in the areas of processors , computer memory , computer storage , and computer networks . The concept of a database was made possible by the emergence of direct access storage media such as magnetic disks , which became widely available in the mid-1960s; earlier systems relied on sequential storage of data on magnetic tape . The subsequent development of database technology can be divided into three eras based on data model or structure: navigational , SQL/ relational , and post-relational. The two main early navigational data models were

4002-423: The type(s) of computer they run on (from a server cluster to a mobile phone ), the query language (s) used to access the database (such as SQL or XQuery ), and their internal engineering, which affects performance, scalability , resilience, and security. The sizes, capabilities, and performance of databases and their respective DBMSs have grown in orders of magnitude. These performance increases were enabled by

4071-410: The underlying database model , with RDBMS for the relational , OODBMS for the object (oriented) and ORDBMS for the object–relational model . Other extensions can indicate some other characteristics, such as DDBMS for a distributed database management systems. The functionality provided by a DBMS can vary enormously. The core functionality is the storage, retrieval and update of data. Codd proposed

4140-455: The use of a "database management system" (DBMS), which is an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information

4209-460: The use of a "language" for data access , known as QUEL . Over time, INGRES moved to the emerging SQL standard. IBM itself did one test implementation of the relational model, PRTV , and a production one, Business System 12 , both now discontinued. Honeywell wrote MRDS for Multics , and now there are two new implementations: Alphora Dataphor and Rel. Most other DBMS implementations usually called relational are actually SQL DBMSs. In 1970,

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4278-574: The word server in computing comes from queueing theory , where it dates to the mid 20th century, being notably used in Kendall (1953) (along with "service"), the paper that introduced Kendall's notation . In earlier papers, such as the Erlang (1909) , more concrete terms such as "[telephone] operators" are used. In computing, "server" dates at least to RFC 5 (1969), one of the earliest documents describing ARPANET (the predecessor of Internet ), and

4347-443: Was ICL 's CAFS accelerator, a hardware disk controller with programmable search capabilities. In the long term, these efforts were generally unsuccessful because specialized database machines could not keep pace with the rapid development and progress of general-purpose computers. Thus most database systems nowadays are software systems running on general-purpose hardware, using general-purpose computer data storage. However, this idea

4416-538: Was a development of software written for the Apollo program on the System/360 . IMS was generally similar in concept to CODASYL, but used a strict hierarchy for its model of data navigation instead of CODASYL's network model. Both concepts later became known as navigational databases due to the way data was accessed: the term was popularized by Bachman's 1973 Turing Award presentation The Programmer as Navigator . IMS

4485-412: Was also read and Mimer SQL was developed in the mid-1970s at Uppsala University . In 1984, this project was consolidated into an independent enterprise. Another data model, the entity–relationship model , emerged in 1976 and gained popularity for database design as it emphasized a more familiar description than the earlier relational model. Later on, entity–relationship constructs were retrofitted as

4554-403: Was different from programs like BASIC, C, FORTRAN, and COBOL in that a lot of the dirty work had already been done. The data manipulation is done by dBASE instead of by the user, so the user can concentrate on what he is doing, rather than having to mess with the dirty details of opening, reading, and closing files, and managing space allocation." dBASE was one of the top selling software titles in

4623-422: Was more interested in the difference in semantics: the use of explicit identifiers made it easier to define update operations with clean mathematical definitions, and it also enabled query operations to be defined in terms of the established discipline of first-order predicate calculus ; because these operations have clean mathematical properties, it becomes possible to rewrite queries in provably correct ways, which

4692-422: Was picked up by two people at Berkeley, Eugene Wong and Michael Stonebraker . They started a project known as INGRES using funding that had already been allocated for a geographical database project and student programmers to produce code. Beginning in 1973, INGRES delivered its first test products which were generally ready for widespread use in 1979. INGRES was similar to System R in a number of ways, including

4761-490: Was to organize the data as a number of " tables ", each table being used for a different type of entity. Each table would contain a fixed number of columns containing the attributes of the entity. One or more columns of each table were designated as a primary key by which the rows of the table could be uniquely identified; cross-references between tables always used these primary keys, rather than disk addresses, and queries would join tables based on these key relationships, using

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