SAP HANA

SAP HANA                                     

Sap Hana is a modern, in memory database and platform that is deployable on premise or in the cloud.

The sap Hana platformis a flexible data source agnostic in memory data platform that allows customers to analyse large volumes of data in real time.it is also a development platform, providing an infrastructure and tools for building high performance application based on sap Hana extended application services (SAP HANA XS). It is the foundation of various SAP HANA editions, like the SAP HANA platform edition, providing core database technology. And the sap Hana enterprise edition, bundling additional components for data provisioning. Thesap Hana platform edition integrates a number of sap components including sap Hana database, SAP Hana studio and SAP Hana clients.

Overview

SAP HANA is acombination of HANA Database, Data Modelling, HANA Administration and Data Provisioning in one single suite. In SAP HANA, HANA stands for High-Performance Analytic Appliance. According to former SAP executive, Dr. Vishal Sikka, HANA stands for Hasso’s New Architecture. HANA developed interest by mid-2011 and various fortune 500 companies started considering it as an option to maintain Business Warehouse needs after that.

Need for SAP HANA

Today, most successful companies respond quickly to market changes and new

Opportunities. A key to this is the effective and efficient use of data and information by

Analyst and managers.

·         HANA overcomes the limitations mentioned below:

·     Due to increase in “Data Volume”, it is a challenge for the companies to provide access to real time     data for analysis and business use.

·        It involves high maintenance cost for IT companies to store and maintain large data volumes.

·            Due to unavailability of real time data, analysis and processing results are delayed.

Features of In-Memory Database

The main features of SAP HANA in-memory database are:

SAP HANA is Hybrid In-memory database.

· It combines row based, column based and Object Oriented base technology.

· It uses parallel processing with multicore CPU Architecture.

· Conventional Database reads memory data in 5 milliseconds. SAP HANA In-Memory database reads data in 5 nanoseconds.

Advantages of In-Memory Database

· HANA database takes advantage of in-memory processing to deliver the fastest data retrieval speeds, which is enticing to companies struggling with high-scale online transactions or timely forecasting and planning.

· Disk-based storage is still the enterprise standard and price of RAM has been declining steadily, so memory-intensive architectures will eventually replace slow, mechanical spinning disks and will lower the cost of data storage.

· In-Memory Column-based storage provides data compression up to 11 times, thus, reducing the storage space of huge data.

· This speed advantages offered by RAM storage system are further enhanced by the use of multi-core CPUs, multiple CPUs per node and multiple nodes per server in a distributed environment.

Access the data you need in real time – with SAP HANA in-memory database services

At the core, SAP HANA is a relational database management system (RDBMS). It combines OLAP and OLTP processing into a single in-memory database – eliminating disk bottlenecks and offering ground-breaking performance. This ACID-compliant, in-memory columnar database stores compressed data, offers parallel processing across multiprocessor cores, and supports single instruction multiple data (SIMD) commands.

SAP HANA Vendors

The few vendor includes

· IBM

· Dell

· HP

· Cisco

· Fujitsu

· Lenovo (China)

· NEC
· Huawei

SAP HANA Modelling

SAP HANA Modeller option is used to create Information views on the top of schemas-> tables in HANA database. These views are consumed by JAVA/HTML based applications or SAP Applications like SAP Lumia, Office Analysis or third party software like MS Excel for reporting purpose to meet business logic and to perform analysis and extract information.

HANA Modelling is done on the top of tables available in Catalog tab under Schema in HANA studio and all views are saved under Content table under Package. You can create new Package under Content tab in HANA studio using right click on Content and New. All Modelling Views created inside one package comes under the same package in HANA studio and categorized according to View Type. Each View has different structure for Dimension and Fact tables. Dim tables are defined with master data and Fact table has Primary Key for dimension tables and measures like Number of Unit sold, Average delay time, Total Price, etc.

SCHEMA IN DATA WAREHOUSE

Schemas are logical description of tables in Data Warehouse. Schemas are created by joining multiple fact and Dimension tables to meet some business logic. Database uses relational model to store data. However, Data Warehouse use Schemas that join dimensions and fact tables to meet business logic. There are three types of Schemas used in a Data Warehouse:

· Star Schema

· Snowflakes Schema

· Galaxy Schema

Star Schema

In Star Schema, Each Dimension is joined to one single Fact table. Each Dimension is represented by only one dimension and is not further normalized. Dimension Table contains set of attribute that are used to analyse the data.

EXAMPLE.

Snowflakes Schema

In Snowflakes schema, some of Dimension tables are further, normalized and Dim tables are connected to single Fact Table. Normalization is used to organize attributes and tables of database to minimize the data redundancy. Normalization involves breaking a table into less redundant smaller tables without losing any information and smaller tables are joined to Dimension table.

Galaxy Schema

In Galaxy Schema, there are multiple Fact tables and Dimension tables. Each Fact table stores primary keys of few Dimension tables and measures/facts to do analysis.

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