Database Management Systems. Overview of Database Systems

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1 Database Management Systems Overview of Database Systems 1

2 Overview of DB Systems Objectives and Outline to study The definition of database systems The importance of database systems Data abstraction and database models Database languages Database system components Users and creators of database systems Database products and applications Database research and trends 2

3 Database Systems: Definition A Database System (DBS) consists of A Database (DB) and A Database Management System (DBMS) A Database is a collection of well-organized and interrelated data A Database Management System is a set of programs to manipulate those data 3

4 Goals of DBMSs To provide a way to store and retrieve database information conveniently and efficiently. DBMSs must meet the following requirements: Data Persistency The data must outlast their creators System Reliability The system must be able to recover correctly and promptly, if crash Scalability The system must be able to handle large numbers of data and lots of users 4

5 Management of Data DBMSs are responsible for management of data, which involves defining structures for storing information (DDL) providing mechanisms for manipulating information (DML) ensuring the safety of the information stored, despite system crashes (System Reliability) or attempts at unauthorized access (System Security) avoiding possible anomalous results if / when data are to be shared among several users (Concurrency Control) supporting large amount of data and concurrent users (Scalability) 5

6 The Importance of DB Systems Before the advent of DB Systems File systems are used to store data. File systems do not provide mechanisms for data management Programmers need to do a lot of data management tasks Defining data structures Manipulating data: inserting, searching, updating, deleting Maintaining data consistency and data integrity Handling data access permission Controlling concurrent data access 6

7 File Systems vs. Database Systems File Systems Data redundancy Difficult data access Integrity problem Atomicity problem Concurrent access anomalies Security problem Long development Tightly-couple data-program relationship Database Systems Data consistency Simple data access Integrity constraint Ensure atomicity Concurrency control Authorization mechanism Short development Data independence 7

8 Disadvantages of DB Systems Do not use a DB system if Overhead of using a DB the DBMS does not support system the types of queries or installation / configuration functionality required by the applications overhead since the DBMS cannot fulfill difficult to setup the needs operating overhead e.g., presentation, calculation concurrency control, transaction support, atomicity and durability persistent storage, and guarantee, etc. many other dominant price features that the DBMS hardware, software, provides are not needed maintenance, and support since the DBMS imposes too high overhead e.g., data caching, logging 8

9 Data Abstraction A major purpose of a database system is to provide users with an abstract view of the data. The system hides certain details of how the data are stored and maintained. For ease of use, simple user interfaces are provided to users. For efficiency, complex data structures are used to represent data in the database. 9

10 View of Data There are multiple levels of data abstraction. E.g., Data of a person can be viewed as High-level: medical records, academic background Intermediate-level: name (alphabetic), age (numeric), gender (enumeration: Male/Female) Low-level: sequences of bits, bytes, and blocks In 1978, ANSI/SPARC architecture defines three levels of data abstraction External Level (View) Conceptual Level (Logical) Internal Level (Physical) 10

11 ANSI/SPARC Architecture In ANSI/SPARC Architecture, a database contains View schemas describe different views of the database (External Level) Logical schema describes the design at the logical level (Conceptual Level) Physical schema describes the design at the physical level (Internal Level) A Schema of a database Is the overall structures of the data in the database and their relationships Schemas change infrequently while data change consistently. 11

12 Levels of Data Abstraction View Level only parts of the entire database Logical Level what data are stored in the database and what relationships exist among those data. Physical Level how data are actually stored 12

13 Data Independence DBMS Data Independence Lower-level schema changes will not effect upper-level schemas and applications Physical Data Independence if physical schema changes do not affect application programs. That is, application programs do not depend on physical schema (but depend on a logical schema or a view schema). Logical Data Independence if logical schema changes do not affect application programs. That is, application programs do not depend on logical schema (but depend on some views). 13

14 DB Models and History 1961, Charles Bachman (1973 Turing Award) designed GE s Integrated Data Store: IDS the predecessor of Network Model. Late 1960s, IBM built Information Management System: IMS Hierarchical Model. Late 1960s, CODASYL group defined/standardized Network Model. 1969, Relational Model by Edgar Codd [IBM] (1981 Turing Award). 1970s, SEQUEL (SQL), QBE; QUEL, System R (DB2), Ingres 1976, Entity-Relationship Model by Peter Chen 1980s, DB2, Oracle, Sybase, Informix, DBase, Paradox, 1986, SQL Standard 1980s, distributed databases 1998, James Gray received Turing Award in Transaction Management. 1990s-2000s, OODB, ORDB (Postgres); Data Warehouse, OLAP, Data Mining, GIS, Mobile DB, Multimedia DB, Web DB, XML DB, 14

15 Data Models Hierarchical Model the first DB model e.g., IMS, System 2000 Network Model DBTG standard; after IDS e.g., IDMS, Total, Relational Model the most widely used now e.g., System R, Ingres, Entity-Relationship Model a conceptual model Object-Oriented Model mostly for special purposes e.g., ObjectStore, Gemstone, Ontos, O2, Jasmine, Cache, Object-Relational Model extends the relational model e.g., Postgres, Informix, DB2, Oracle, *Semi-structured Data* focus on data in XML format 15

16 Data Models Diagrams Hierarchical and Network customer name address account number balance customer account own name address number balance Network data-structure diagram virtual account virtual customer Hierarchical tree-structure diagram customer name address custlink account number balance acctlink dummy DBTG data-structure diagram 16

17 Data Models Diagrams Relational, ER, OO name address number balance customer own account customer # name address owner # name # number account # number balance Entity-Relationship diagram Relational schema diagram customer name address 1..* 0..* account number balance UML class diagram (OO Model) 17

18 Database Languages Data Definition Language (DDL) to specify the database schema. Database schemas are stored in the data dictionary. The data dictionary contains metadata. Metadata: data about data, e.g. schema. Data Manipulation Language (DML) to express database queries and updates (include insertion, deletion, and modification) Procedural DMLs -and- Declarative DMLs 18

19 DB Languages: Examples Hierarchical Model (DL/I): DML: get first customer where customer.name:= Henry ; Network Model (DBTG): DDL: set name is custlink owner is customer member is dummy; DML: customer.name := Newton ; find any customer using name; get customer; print(customer.address); 19 Relational Model (SQL): DDL: create table customer ( name char(30), address char(60)); DML: select address from customer where name likes Robert ; Object-Oriented Model (ODMG): DDL: class customer:public object { string name; string address; set<ref<account>> accounts; };

20 Data Manipulation Languages Procedural DMLs require a user to specify what data are needed and how to get those data e.g., relational algebra; (C, Pascal, Java, etc.) Declarative DMLs (nonprocedural DMLs) require a user to specify what data are needed without specifying how to get those data e.g. relational tuple calculus, relational domain calculus, SQL (core), Quel, QBE, Datalog; (Prolog) A Query Language is a part of DML that involves only retrieval of information (without updates) However, a query language often means DML 20

21 What are the components of DBMSs? A database system is partitioned into modules that deal with each of the responsibilities of the overall system. The functional components of a database system can be broadly divided into the Query Processor Component: to simplify and facilitate access to data (convenient and efficient) the Storage Manager Component: to minimize the need to move data between disk and main memory the Transaction Manager Component: to handle atomicity and concurrency of transactions and consistency and durability of the databases 21

22 Query Processor Component Query Processor: A program module that provides the interface between the database and the application programs/queries Components include: DDL interpreter interprets DDL commands and records them in the data dictionary DML compiler translates DML commands into query evaluation plans Query evaluation engine executes queries according to the plans 22

23 Storage Manager Component A Storage Manager is A program module that provides the interface between the low-level data stored in the database and the application programs/queries submitted to the system Components include: Authorization and integrity manager File manager Buffer manager Structures maintained: data files, data dictionary, indices 23

24 Transaction Manager Component Transaction: a collection of operations that performs as a single logical function in a database application. Transaction Properties: ACID A tomicity: either all operations succeed or all of them fail C onsistency: the database is changed from one consistent state to another consistent state I solation: no transaction interfere other transactions in the middle D urability: operations of successful transactions must persist Components include Transaction Manager Lock Manager Recovery Manager 24

25 DB System Structure application programs queries schemas API module transaction manager concurrency control lock manager DML compiler query processor and optimizer buffer manager storage manager DDL interpreter recovery manager index data data dictionary 25

26 Who interact with DBMSs? Database Administrators (DBAs) Database Operators Database Designers DB Application Developers/Programmers End Users Sophisticated End Users Naïve End Users DB System Designers and Implementers Database Tool Developers 26

27 DB Administrators (DBAs) and DB Operators DBAs are responsible for Starting up and shutting down the databases Loading, importing, exporting data to/from the databases Granting of authorization for using resources Monitoring the use of the resources Backing up the databases periodically and restoring the databases as needed Tuning the system performance Considering software and hardware upgrades DB Operators are responsible for {Helping DBAs maintaining normal DB operations} 27

28 DB Designers and DB Developers / Programmers Database Designers are responsible for Analyzing data requirements Designing the database structures View, logical, and physical structures Creating the databases DB Application Developers / Programmers Analyzing functional requirements Developing program specifications from the requirements Implementing those application programs 28

29 End Users Sophisticated End Users Writing ad hoc queries to answer their own needs Running ad hoc reports for executives/managers Naïve End Users Using customized applications developed by developers/programmers Data entry operators, Executives, managers, 29

30 Participants on the implementation side of the database systems DB System Designers and Implementers Designing the structures and the functions of each component of the DBMSs Implementing database components File organizations, index structures, query processing, transaction management, DB API, user interface, DB Tool Developers Designing and implementing tools for databases Database design tools, application development tools, performance tuning tools, database administration tools, 30

31 Very Important Participants Leaders in DB Industry Oracle ORACLE, RDB IBM DB2, Informix Microsoft SQL Server, Access, FoxPro ODBC, ADO Sybase Sybase Leaders in DB Research Leading Universities Stanford U. UC Berkeley {Ingres, Postgres} U of MD - College Park U of Wisconsin - Madison Research Labs IBM {System R, SQL, } Microsoft Bell Lab Conferences/Journals SIGMOD/POD, VLDB, EDBT, ICDE, RIDE, TKDE, 31

32 DBMS Market Share Windows New Licenses Revenue in Billion USD Revenue ORACLE 40.4% 2.4 B 38.1% 2.5 B 34.0% IBM 15.2% 19.9% 20.7% Revenue B B B Microsoft 35.2% 35.4% 39.9% ORACLE 31.4% 33.8% 32.0% Unix IBM 29.9% 30.1% 34.6% Revenue 3.6 B 3.0 B Microsoft 13.1% 14.9% 16.3% ORACLE 66.2% 63.3% Sybase? 3.2% 2.6% IBM 14.4% 24.7% Informix? 3.0% Informix 6.7% 32 Source: Gartner Dataquest

33 Some Database Related Products Commercial Products Relational: Access, DB2, DBASE, FoxPro, Informix, Interbase, ORACLE, Paradox, RDB, SQL Server, Sybase, ThinkDB, UniSQL, etc. OO: Cachè, Exodus, Gemstone, Iris, Jasmine, O 2, Objectivity, ObjectStore, ODE, ONTOS, Orion, Versant, etc. Hierarchical: IMS Free/Open Source Products Ingres, msql, MySQL, Postgres, etc. Database APIs ODBC, JDBC, ADO, 33

34 Examples of DB System Applications Accounting Airlines Banking Finance Hospitals Human Resources Inventory Manufacturing Telecommunication Tourism Transportation Sales Universities (you name it) 34

35 Trends of Database Products Past and Present: to support large amount of data and concurrent users data management of well-structured data on-line transaction processing (OLTP) Scalability Present and Future: A Complete System multimedia/complex data management advanced OLTP: workflow application development tools data repository: warehouse, data mart data analysis tools: Online Analytical Processing (OLAP) Data Mining a well-rounded system web-enable, network-enable, XML-compliant, multi-model 35

36 DBMS Architectures Based on the number of users: Single-user Systems Only one user (one session) uses the system at a time Multi-user Systems Multiple users use the system at the same time Based on the locations of the databases and their users Stand-alone DBMSs One DBMS supports its user(s) on the same machine Client-Server (Centralized) DBMSs One database server serves multiple clients Distributed DBMSs Coordination of multiple DBMSs 36

37 Distributed DB Systems Distributed DBMSs Homogeneous Database Systems Multiple subsystems which are of the same architectures spread around multiple remote sites E.g., A system of multiple ORACLE on multiple computers at multiple remote sites Heterogeneous Database Systems Multiple systems which are of different architectures E.g., A system of one DB2 + one SQL Server Federated Database Systems Also known as Multidatabase Systems A kind of Heterogeneous Database Systems where each DBMS of the whole system has their own autonomy 37

38 Distributed DBMSs ORACLE Homogeneous ORACLE SQL Server Federated DBMS Heterogeneous ORACLE ORACLE DB2 38

39 DB Application Architectures Client-Server (C/S) Client machine: the database users work Server machine: the database system runs C/S: Two-tier architecture: small systems Client: the DB users and the DB application Server: the DB system C/S: Three-tier architecture: large systems, web Client sends requests to the application server Application Server runs the application as a server for the client and as a client of the database server Database Server runs the DBMS 39

40 Client/Server Architecture Two-Tier Architecture Database Layer 1 Application Layer Three-Tier Architecture 2 Database Layer 2 1 Presentation Layer 3 Business Logic Layer 4 40

41 What architectures are they? A DBMS on a mainframe with multiple users; one on each terminal? A DBMS on a PC running a web server that accesses the DBMS to provide services to its users? A system connecting DBMSs of multiple companies together? A system with a java application running on a web browser that sends requests to the web server which accesses a database on another machine? 41

42 Specialized/Advanced DBMSs Active DB Systems Data Warehouses Deductive DB Systems Genome DB Systems Geographic Information Systems Main Memory DB Systems Mobile DB Systems Multimedia DB Systems Parallel DBMSs Text DB Systems Temporal DB Systems Spatial DB Systems Spatio-temporal DB Systems XML DB Systems 42

43 Conclusion Questions and Answers 43

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