Introduction about Essbase

Essbase stands for Extended SpreadSheet dataBASE.

Essbase is a multi-threaded OLAP database software that takes advantage of symmetric multiprocessing hardware platforms - is based on Web-deployable, thin-client architecture. The server acts as a shared resource, handling all data storage, caching, calculations, and data security.

Essbase Architecture

Essbase product incorporate powerful architecture feature to handle a wide range of analytic application across the large multiuser environments.

Essbase product family feature a middle tier architecture to handle a wide range of analytic application across large multiple-user environments.

The database tier consists of Essbase Server (where Essbase database are stored) and any relational databases that you are using to support Essbase environment.

The client tier includes locally installed client application, such as EAS & Smart View

The middle tier includes application services that facilitates the communication and data transfer between the database tier and client tier.

Essbase Storage Models

Essbase supports two storage types: Block Storage (BSO) and Aggregate Storage (ASO). Essbase can support many different business model by using these two models.

Below screen shot provide you a partial list of business analyses that you can model in Essbase, with suggestion for the storage type that best meets the challenge of each business model.

Block Storage

Block Storage databases are optimized for data set that are partially dense. Data is stored in dense data blocks which are indexed along sparse dimension for retrieval.

This storage paradigm enables you to perform:

• Top down budgeting and planning
• In addition to sophisticated pre-aggregation calculations

Aggregation Storage

Aggregate storage database are optimized for sparse data set that primarily require simple aggregation. Any non-aggregation calculations are performed dynamically when requested in reports. Incremental loading and fast aggregation can provide near real-time analysis of transactional data.

Aggregate storage databases enable dramatic improvements in both:

• Database aggregation time
• Dimensional scalability.