OLAP is considered (Online Analytical Processing) which is a type of software that helps in analyzing information from multiple databases at a particular time. OLAP is simply a multidimensional data model and also applies querying to it.
Types of OLAP Servers
- Relational OLAP
- Multi-Dimensional OLAP
- Hybrid OLAP
- Transparent OLAP
Relational OLAP (ROLAP): Star Schema Based
The ROLAP is based on the premise that data need not be stored multi-dimensionally to be viewed multi-dimensionally, and that it is possible to exploit the well-proven relational database technology to handle the multidimensionality of data. In ROLAP data is stored in a relational database. In essence, each action of slicing and dicing is equivalent to adding a “WHERE” clause in the SQL statement. ROLAP can handle large amounts of data. ROLAP can leverage functionalities inherent in the relational database.
Multidimensional OLAP (MOLAP): Cube-Based
MOLAP stores data on disks in a specialized multidimensional array structure. OLAP is performed on it relying on the random access capability of the arrays. Arrays elements are determined by dimension instances, and the fact data or measured value associated with each cell is usually stored in the corresponding array element. In MOLAP, the multidimensional array is usually stored in a linear allocation according to nested traversal of the axes in some predetermined order.
But unlike ROLAP, where only records with non-zero facts are stored, all array elements are defined in MOLAP and as a result, the arrays generally tend to be sparse, with empty elements occupying a greater part of it. Since both storage and retrieval costs are important while assessing online performance efficiency, MOLAP systems typically include provisions such as advanced indexing and hashing to locate data while performing queries for handling sparse arrays. MOLAP cubes are fast data retrieval, optimal for slicing and dicing, and can perform complex calculations. All calculations are pre-generated when the cube is created.
Hybrid OLAP (HOLAP)
HOLAP is a combination of ROLAP and MOLAP. HOLAP servers allow for storing large data volumes of detailed data. On the one hand, HOLAP leverages the greater scalability of ROLAP. On the other hand, HOLAP leverages cube technology for faster performance and summary-type information. Cubes are smaller than MOLAP since detailed data is kept in the relational database. The database is used to store data in the most functional way possible.
Transparent OLAP (TOLAP)
TOLAP systems are designed to work transparently with existing RDBMS systems, allowing users to access OLAP features without needing to transfer data to a separate OLAP system. This allows for more seamless integration between OLAP and traditional RDBMS systems.
Other Types of OLAP
There are some other types of OLAP Systems that are used in analyzing databases. Some of them are mentioned below.
- Web OLAP (WOLAP): It is a Web browser-based technology. In traditional OLAP application is accessible by the client/server but this OLAP application is accessible by the web browser. It is a three-tier architecture that consists of a client, middleware, and database server. The most appealing features of this style of OLAP were (past tense intended, since few products categorize themselves this way) the considerably lower investment involved on the client side (“all that’s needed is a browser”) and enhanced accessibility to connect to the data. A Web-based application requires no deployment on the client machine. All that is needed is a Web browser and a network connection to the intranet or Internet.
- Desktop OLAP (DOLAP): DOLAP stands for desktop analytical processing. Users can download the data from the source and work with the dataset, or on their desktop. Functionality is limited compared to other OLAP applications. It has a cheaper cost.
- Mobile OLAP (MOLAP): MOLAP is wireless functionality for mobile devices. User work and access the data through mobile devices.
- Spatial OLAP (SOLAP): Merge capabilities of both Geographic Information Systems (GIS) and OLAP into the single user interface, SOLAP egress. SOLAP is created because the data come in the form of alphanumeric, image, and vector. This provides the easy and quick exploration of data that resides in a spatial database.
- Real-time OLAP (ROLAP): ROLAP technology combines the features of both OLTP and OLAP. It allows users to view data in real-time and perform analysis on data as it is being updated in the system. ROLAP also provides a single, unified view of data from different sources and supports advanced analytics like predictive modeling and data mining.
- Cloud OLAP (COLAP): COLAP is a cloud-based OLAP solution that allows users to access data from anywhere and anytime. It eliminates the need for on-premise hardware and software installations, making it a cost-effective and scalable solution for businesses of all sizes. COLAP also offers high availability and disaster recovery capabilities, ensuring business continuity in the event of a disaster.
- Big Data OLAP (BOLAP): BOLAP is an OLAP solution that can handle large amounts of data, such as data from Hadoop or other big data sources. It provides high-performance analytics on large datasets and supports complex queries that are impossible with traditional OLAP tools. BOLAP also supports real-time analysis of big data, allowing users to make informed decisions based on up-to-date information.
- In-memory OLAP (IOLAP): IOLAP is an OLAP solution that stores data in memory for faster access and processing. It provides real-time analysis on large datasets and supports complex queries, making it an ideal solution for businesses that require fast and accurate analytics. IOLAP also supports advanced analytics like predictive modeling and data mining, allowing users to gain insights into their data and make informed decisions.
Advantages of OLAP System
- Fast query response: OLAP systems are designed to provide fast query response times, even for complex queries involving large amounts of data.
- Multidimensional analysis: OLAP systems allow users to analyze data from multiple dimensions, such as time, location, product, and customer, providing a deeper understanding of the data.
- Flexible and customizable: OLAP systems are highly customizable, allowing users to define their dimensions, hierarchies, and calculations.
- Improved decision-making: OLAP systems provide users with the ability to analyze data from different angles, leading to better insights and more informed decision-making.
Disadvantages of the OLAP System
- Complexity: OLAP systems can be complex to implement and maintain, requiring specialized skills and knowledge.
- Data storage requirements: OLAP systems require a large amount of storage space to store multidimensional data, which can be expensive and difficult to manage.
- Limited transactional processing: OLAP systems are optimized for analytical processing, but they are not suitable for transactional processing, which can lead to performance issues.
- Performance degradation with large datasets: As the size of the dataset increases, the performance of OLAP systems may degrade, requiring additional hardware resources to maintain performance.
For more, refer to the Difference Between OLAP and OLTP.
Frequently Asked Questions On OLAP Systems
1. What is OLAP Server?
OLAP Server is basically a software tool in order to easily make data analytics for business models.
2. What are the four main types of OLAP Servers?
The main types of OLAP Servers are listed below.
- Relational OLAP (ROLAP)
- Multidimensional OLAP (MOLAP)
- Hybrid OLAP (HOLAP)
- Transparent OLAP (TOLAP)
3. What are the uses of the OLAP System?
The uses of the OLAP System are mentioned below
- Sales Reporting
- Management Reporting
- Process Management
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