SAP HANA Database Overview

The SAP HANA database is a hybrid in-memory database that combines row-based, column-based, and object-based database technology.

It is optimized to exploit the partial processing capabilities of modem multi-core / CPU architectures. With this architecture, SAP applications can benefit from current bar down technologies.

The SAP HANA database is the heart of SAP’s in-memory technology offering, helping customers to improve their operational efficiency, agility, and flexibility.

SAP HANA Information Composer

SAP HANA Information composer is a Web-Based Environment that allows business users to upload data to the SAP HANA database and to manipulate that data by creating information values.

The main features of information Composer are as follows

Data acquisition

You can upload the data, preview, and cleanse this data, and create a physical table in the SAP HANA database.

Data Manipulation

You can select two objects in the SAP HANA database, combined them, add calculated fields, and create an informed view that can be consumed by SAP Bo tools.

BUSINESS / INTELLIGENCE

(Business Objects) – It is a reporting tool of generating reports from views provided by the HANA Information Composer studio.

We can generate reports from views in two ways

Direct Accessing views for crystal reports, Advanced Analysis, Explorer, Webi4.0, SAP Real-time Salaries

WE can create UDT or IDT (Universe Design tool, Information Design tool) first and then create reports. 

SAP HANA STUDIO

Here we can perform modeling & administration on data which is available in HANA DB and to produce views which are used to create reports and to build a dashboard in the SAP BO tool

Pre-requisite

SAP HANA Hardware

Multicore Architecture/HANA DB

SAP HANA Software

In-Memory Computing Engine Algorithm (Row/Column/Object)

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SAP HANA DB Overview

SQL DBHANA DB

  • Row
  • DB & Application in different architecture
  • SQL
  • Limited cache
  • SQL

  • Row & Colum
  • HANA DB & HANA apps are in the same architecture
  • SQL/MDX
  • For all data
  • SQL/HANA SQL scripts

Advantages of Column level stage

Sligh data compression rate

Sligh performance on column operation

Elimination of Traditional materialized view concept

Elimination of unnecessary index

Normal DBH/WHANA H/W

  • Limited in RAM
  • Disk-based storage

  • Everything we used in RAM
  • Mute core storage

sap hana data table view

In HANA Table schema we have not the only table but also views

In the Analytical view, Attribute view, calculated view these are surrounded by tables and view

Role of HANA studio in HANA Database System

It helps us to create analytically, calculate views

HANA studio also helps us to do the turning of SQL Query & support for ANSI SQL

sap hana database system

Initially the Data ERP BW Mixed Source

Replicated (With Initial data volumes and lock) – It is mapped to HANA DB persistence layer

When we load all data into memory and log volume data will be loading into paging memory with the help of HANA Management System

Once the data loaded into cache memory we will prepare data stores (row/column/object)

These data stores can be optimized.

They can also use standard SQL Statements & scripts to optimized. For that, this is given to HANA studio by request parser to prepare the views (Analytical / Attribute / Calculated views)

We can maintain these views & Datastore in HANA metadata Manager which is given to the reporting analysis

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SAP HANA Security

HANA Landscape has got different levels in different phases

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Database Development

At DB level we define security for view & tables in terms of database repository owners authorization for networks

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Modeling Level

To prepare and process the view, accessing metadata manager, accessing request parser, authorization to add data services as an external system in HANA studios.

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At Reporting level

Authorization for HANA ODBC.

Authorization to create a semantic layer using HANA DB.

Authorization in accessing HANA Views, UNX files (4.0) in generating BO Business Intelligence

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