database management systems

DM-67 - NoSQL Databases

NoSQL databases are open-source, schema-less, horizontally scalable and high-performance databases. These characteristics make them very different from relational databases, the traditional choice for spatial data. The four types of data stores in NoSQL databases (key-value store, document store, column store, and graph store) contribute to significant flexibility for a range of applications. NoSQL databases are well suited to handle typical challenges of big data, including volume, variety, and velocity. For these reasons, they are increasingly adopted by private industries and used in research. They have gained tremendous popularity in the last decade due to their ability to manage unstructured data (e.g. social media data).

DM-03 - Relational DBMS and their Spatial Extensions

The relational Database Management System (DBMS) is widely used in modern business systems. Entities and relationships from a data model are presented as relational tables. To store data in a relational database, a relation schema should be defined to specify the design and structure of relations. The schema design generally uses database normalization to reduce data redundancy and maintain data integrity. Users can retrieve and manage data in a relational database using Structured Query Language (SQL). To make spatial data fit the relational model, spatial vector geometry or raster data type can be customized by extending basic data types in relational databases. This further helps derive the so-called spatial object-relational DBMS, by manipulating vector geometry and/or raster data types as spatial objects using SQL queries. The performance of queries is improved by adding spatial indexes in relational databases.

DM-04 - Object-oriented DBMS
  • Describe the basic elements of the object-oriented paradigm, such as inheritance, encapsulation, methods, and composition
  • Evaluate the degree to which the object-oriented paradigm does or does not approximate cognitive structures
  • Explain how the principle of inheritance can be implemented using an object-oriented programming approach
  • Defend or refute the notion that the Extensible Markup Language (XML) is a form of object-oriented database
  • Explain how the properties of object orientation allows for combining and generalizing objects
  • Evaluate the advantages and disadvantages of object-oriented databases compared to relational databases, focusing on representational power, data entry, storage efficiency, and query performance
  • Implement a GIS database design in an off-the-shelf, object-oriented database
  • Differentiate between object-oriented programming and object-oriented databases
DM-03 - Relational DBMS and their Spatial Extensions

The relational Database Management System (DBMS) is widely used in modern business systems. Entities and relationships from a data model are presented as relational tables. To store data in a relational database, a relation schema should be defined to specify the design and structure of relations. The schema design generally uses database normalization to reduce data redundancy and maintain data integrity. Users can retrieve and manage data in a relational database using Structured Query Language (SQL). To make spatial data fit the relational model, spatial vector geometry or raster data type can be customized by extending basic data types in relational databases. This further helps derive the so-called spatial object-relational DBMS, by manipulating vector geometry and/or raster data types as spatial objects using SQL queries. The performance of queries is improved by adding spatial indexes in relational databases.

DM-67 - NoSQL Databases

NoSQL databases are open-source, schema-less, horizontally scalable and high-performance databases. These characteristics make them very different from relational databases, the traditional choice for spatial data. The four types of data stores in NoSQL databases (key-value store, document store, column store, and graph store) contribute to significant flexibility for a range of applications. NoSQL databases are well suited to handle typical challenges of big data, including volume, variety, and velocity. For these reasons, they are increasingly adopted by private industries and used in research. They have gained tremendous popularity in the last decade due to their ability to manage unstructured data (e.g. social media data).

DM-03 - Relational DBMS
  • Explain the advantage of the relational model over earlier database structures including spreadsheets
  • Define the basic terms used in relational database management systems (e.g., tuple, relation, foreign key, SQL, relational join)
  • Discuss the efficiency and costs of normalization
  • Describe the entity-relationship diagram approach to data modeling
  • Explain how entity-relationship diagrams are translated into relational tables
  • Create an SQL query that extracts data from related tables
  • Describe the problems associated with failure to follow the first and second normal forms (including data confusion, redundancy, and retrieval difficulties)
  • Demonstrate how search and relational join operations provide results for a typical GIS query and other simple operations using the relational DBMS within a GIS software application
DM-04 - Object-oriented DBMS
  • Describe the basic elements of the object-oriented paradigm, such as inheritance, encapsulation, methods, and composition
  • Evaluate the degree to which the object-oriented paradigm does or does not approximate cognitive structures
  • Explain how the principle of inheritance can be implemented using an object-oriented programming approach
  • Defend or refute the notion that the Extensible Markup Language (XML) is a form of object-oriented database
  • Explain how the properties of object orientation allows for combining and generalizing objects
  • Evaluate the advantages and disadvantages of object-oriented databases compared to relational databases, focusing on representational power, data entry, storage efficiency, and query performance
  • Implement a GIS database design in an off-the-shelf, object-oriented database
  • Differentiate between object-oriented programming and object-oriented databases
DM-67 - NoSQL Databases

NoSQL databases are open-source, schema-less, horizontally scalable and high-performance databases. These characteristics make them very different from relational databases, the traditional choice for spatial data. The four types of data stores in NoSQL databases (key-value store, document store, column store, and graph store) contribute to significant flexibility for a range of applications. NoSQL databases are well suited to handle typical challenges of big data, including volume, variety, and velocity. For these reasons, they are increasingly adopted by private industries and used in research. They have gained tremendous popularity in the last decade due to their ability to manage unstructured data (e.g. social media data).

DM-04 - Object-oriented DBMS
  • Describe the basic elements of the object-oriented paradigm, such as inheritance, encapsulation, methods, and composition
  • Evaluate the degree to which the object-oriented paradigm does or does not approximate cognitive structures
  • Explain how the principle of inheritance can be implemented using an object-oriented programming approach
  • Defend or refute the notion that the Extensible Markup Language (XML) is a form of object-oriented database
  • Explain how the properties of object orientation allows for combining and generalizing objects
  • Evaluate the advantages and disadvantages of object-oriented databases compared to relational databases, focusing on representational power, data entry, storage efficiency, and query performance
  • Implement a GIS database design in an off-the-shelf, object-oriented database
  • Differentiate between object-oriented programming and object-oriented databases
DM-03 - Relational DBMS
  • Explain the advantage of the relational model over earlier database structures including spreadsheets
  • Define the basic terms used in relational database management systems (e.g., tuple, relation, foreign key, SQL, relational join)
  • Discuss the efficiency and costs of normalization
  • Describe the entity-relationship diagram approach to data modeling
  • Explain how entity-relationship diagrams are translated into relational tables
  • Create an SQL query that extracts data from related tables
  • Describe the problems associated with failure to follow the first and second normal forms (including data confusion, redundancy, and retrieval difficulties)
  • Demonstrate how search and relational join operations provide results for a typical GIS query and other simple operations using the relational DBMS within a GIS software application

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