Cubes
Cubes are data processing units composed of fact tables and dimensions from the data warehouse. They provide multidimensional views of data, querying and analytical capabilities to clients. A cube can be stored on a single analysis server and then defined as a linked cube on other Analysis servers. End users connected to any of these analysis servers can then access the cube. This arrangement avoids the more costly alternative of storing and maintaining copies of a cube on multiple analysis servers. linked cubes can be connected using TCP/IP or HTTP. To end users a linked cube looks like a regular cube.Linked cube are cubes in which a sub-set of the data can be analysed into great detail. The linking ensures that the data in the cubes remain consistent.
Cubes are data processing units composed of fact tables and dimensions from the data warehouse. They provide multidimensional views of data, querying and analytical capabilities to clients. A cube can be stored on a single analysis server and then defined as a linked cube on other Analysis servers. End users connected to any of these analysis servers can then access the cube. This arrangement avoids the more costly alternative of storing and maintaining copies of a cube on multiple analysis servers. linked cubes can be connected using TCP/IP or HTTP. To end users a linked cube looks like a regular cube.Linked cube are cubes in which a sub-set of the data can be analysed into great detail. The linking ensures that the data in the cubes remain consistent.
OLAP cubes
These are OLAP cubes created by clients, end users or third-party applications accessing a data warehouse, relational database or OLAP cube through the Microsoft® PivotTable® Service. E.g. Microsoft® Excel™ is very popular as a client for creating offline local OLAP cubes from relational databases for multidimensional analysis. These cubes have to be maintained and managed by the end users who have to manually refresh their data.
PivotTable® Service
This is the primary component that connects clients to the Microsoft® SQL Server™ 2000 Analysis Server. It also provides the capability for clients to create local offline cubes using it as an OLAP server. PivotTable® Service does not have a user interface, the clients using its services has to provide its user interface.
These are OLAP cubes created by clients, end users or third-party applications accessing a data warehouse, relational database or OLAP cube through the Microsoft® PivotTable® Service. E.g. Microsoft® Excel™ is very popular as a client for creating offline local OLAP cubes from relational databases for multidimensional analysis. These cubes have to be maintained and managed by the end users who have to manually refresh their data.
PivotTable® Service
This is the primary component that connects clients to the Microsoft® SQL Server™ 2000 Analysis Server. It also provides the capability for clients to create local offline cubes using it as an OLAP server. PivotTable® Service does not have a user interface, the clients using its services has to provide its user interface.
Virtual cubes
These are combinations of one or more real cubes and require no disk space to store them. They store only the definitions and not the data of the referenced source cubes. They are similar to views in relational databases.
These are combinations of one or more real cubes and require no disk space to store them. They store only the definitions and not the data of the referenced source cubes. They are similar to views in relational databases.
MOLAP cubes
MOLAP Cubes: stands for Multidimensional OLAP. In MOLAP cubes the data aggregations and a copy of the fact data are stored in a multidimensional structure on the Analysis Server computer. It is best when extra storage space is available on the Analysis Server computer and the best query performance is desired. MOLAP local cubes contain all the necessary data for calculating aggregates and can be used offline. MOLAP cubes provide the fastest query response time and performance but require additional storage space for the extra copy of data from the fact table.ROLAP cubes
ROLAP Cubes: stands for Relational OLAP. In ROLAP cubes a copy of data from the fact table is not made and the data aggregates are stored in tables in the source relational database. A ROLAP cube is best when there is limited space on the Analysis Server and query performance is not very important. ROLAP local cubes contain the dimensions and cube definitions but aggregates are calculated when they are needed. ROLAP cubes require less storage space than MOLAP and HOLAP cubes.
HOLAP cubes
HOLAP Cubes: stands for Hybrid OLAP. A ROLAP cube has a combination of the ROLAP and MOLAP cube characteristics. It does not create a copy of the source data however, data aggregations are stored in a multidimensional structure on the Analysis Server computer. HOLAP cubes are best when storage space is limited but faster query responses are needed.
MOLAP Cubes: stands for Multidimensional OLAP. In MOLAP cubes the data aggregations and a copy of the fact data are stored in a multidimensional structure on the Analysis Server computer. It is best when extra storage space is available on the Analysis Server computer and the best query performance is desired. MOLAP local cubes contain all the necessary data for calculating aggregates and can be used offline. MOLAP cubes provide the fastest query response time and performance but require additional storage space for the extra copy of data from the fact table.ROLAP cubes
ROLAP Cubes: stands for Relational OLAP. In ROLAP cubes a copy of data from the fact table is not made and the data aggregates are stored in tables in the source relational database. A ROLAP cube is best when there is limited space on the Analysis Server and query performance is not very important. ROLAP local cubes contain the dimensions and cube definitions but aggregates are calculated when they are needed. ROLAP cubes require less storage space than MOLAP and HOLAP cubes.
HOLAP cubes
HOLAP Cubes: stands for Hybrid OLAP. A ROLAP cube has a combination of the ROLAP and MOLAP cube characteristics. It does not create a copy of the source data however, data aggregations are stored in a multidimensional structure on the Analysis Server computer. HOLAP cubes are best when storage space is limited but faster query responses are needed.
HOLAP Cubes: stands for Hybrid OLAP. A ROLAP cube has a combination of the ROLAP and MOLAP cube characteristics.
ReplyDeleteHere in place of ROLAP i believe HOLAP is required