Webinar: SAP HANA - Features, Architecture and Advantages

Presented By

Abhishek Sur Solution Architect, InSync Solutions

Microsoft MVP

Agenda • Introduction to SAP HANA • Architecture • Key benefits which lead to SAP HANA as backend database system.

• Difference between SAP HANA with other traditional RDBMS

• Few use Cases • Column Store vs Row based storage • Multiple Engines • Limitations

Introduction • SAP HANA is the in-memory analytic product which can help companies to do ad hoc analysis of business data in real time.

• HANA is designed to deliver data in real time after analyzing large volumes of data.

• It is completely re-imagined for real time business.

• HANA transforms business by streamlining transaction, analytics, planning and predictive data processing on a single in-memory database so that the business can operate in real time.

• SAP HANA is developed in C++ and runs on SUSE Linux Enterprise Server

HANA Architecture SQL Passed either directly or using HANA Client Library

Index Server • This is the most important server that SAP HANA should have. This is mandatory server component.

• Deals with Actual data stores and data processing engine • Deals with Persistent storage to selectively store data and transaction logs in background.

• Contains Processing engine which processes and validates SQL or MDX statements in the context of authenticated session and transactions.

SAP HANA Database Index Server

Components Persistent Layer

Relational Data Engine

• This layer is to ensure durability and

• Relational data engine is responsible of

atomicity of transactions • Keeps track of committed state and writes to disk.

• During restart this layer restores the most recent committed transaction state and clears uncommitted transactions.

• Capable of storing transaction logs during or after transaction is committed or completely

undone.

determining the storage mechanism of data.

• It either chooses Row store or Column store for

data storage.

Components Connection and Session Management

Authorization maangement

• Authenticates a client to generate session.

• Invoked by HANA to check whether the user has

• Maintains a set of parameters per session like auto-commit, current transaction, isolation level etc.

• Authentication based either by HANA database itself or can be delegated to

external providers.

required priviledges for requested resource.

• Allows to grant permission for operation or for specific object to an user.

• Can also restrict by dimension attribute

Components Planning Engine

Calc Engine

• Planning engine is capable of

• Creates logical plan for calculation

determining the data planning during transformation.

• For example, during new year, the

planning engine can generate a copy of the data object while applying filters.

• Determining different aggregation levels

during query execution.

• It creates calculation models from domain specific models.

• The calculation engine is responsible for accuracy of data.

Pre-Processor Server • Preprocessor server is used for analyzing textual data. • For any request, the Preprocessor server analyses the data to extract information from text data.

Name Server • Maintains System landscape information of the HANA System • It handles the topology of the server for a distributed database.

• It decreases the time for re-indexing as it holds which data is on which server.

Statistical Server • Checks and analyzes the health of all components in HANA. • Statistical server is responsible for collecting data related to system resources, allocation of resources, consumption of resources and also checks overall performance of the system.

• It stores historical data related to system performance which can be fetched

for analysis purpose.

Benefits of SAP HANA • Best suited for Analytics data.

• Best in breed for In-memory computing • Empowers business users as opposed to developer.

• Because most of the data reside in memory, it is said to be 3600 times faster than traditional databases.

• It is a popular choice as a backend for SAP systems.

• SAP HANA is also available in Cloud.

• Compression is in-built which reduces the space requirements dramatically in HANA.

Difference Between HANA and Traditional Databases HANA Database

Traditional Database

•

Entire data is loaded in memory

•

Entire data is stored in disk

•

Allows column based as well as row based data storage

•

All data is in row based data storage.

•

Support massive parallel processing.

•

Generally only one core is responsible for one query execution.

•

OLAP queries performs best in HANA.

•

OLAP queries require to load all data to perform operation.

•

Performance is gained normally for analytical data

•

Performance is gained by de-normalizing and redundancy of data for

analytical purposes.

Use Cases of HANA Sales Reporting (CRM) •

Quickly identify top customers and products by channel – with real –time sales reporting. Improve order fulfillment rates and accelerate.

•

Key sales processes at the same time, with instant analysis of credit memo and billing list.

Financial Reporting (FICO) •

Obtain immediate insights across your business into review, accounts payable and receivable, open and overdue items.

•

Top general ledger transaction and days sales outstanding. Make the right financial decision, armed with real time information.

Shipping Reporting (LE – SHP) •

•

Rely on real-time shipping reporting for complete stock overview analysis. One can better plan/monitor outbound delivery.

Assess and optimize stock levels – with accurate information at one’s fingertip

Purchase Reporting (P2P/SRM) •

Gain timely insights into purchase orders, vendors, and the movement of goods- with real time purchase reporting.

•

Make better purchasing decisions based on a complete analysis of order history.

Master Data Reporting (DG / MDM) •

Obtain real time reporting on main master data, including customer, vendor, and material lists for improved productivity and accuracy.

Different storage options Column Store

Row Store

• All columnar data is stored in contiguous location.

• Data from same row is stored in contiguous location.

• Columnar store is read optimized.

• Row store is write optimized.

• Only required data could be loaded. This

• All record needs to be loaded while primary key and indexes performs a vital role.

is called data stripping.

• Optimization of data could be made based on data type of a particular column

• Optimization based on data type is not possible.

Multiple Engines • HANA has multiple engines inside its computing engine for better performance. • HANA Supports both SQL & OLAP reporting tools, there are separate engines to

perform operation respectively. • Each request is broken into multiple pieces and the same is sent to specific engine for processing. The HANA SQL Engine acts as a controller to parse and send the same to multiple engines for request processing.

Demo

Disadvantages of using SAP HANA • Its too expensive.

• You cannot hold a lot of data in it. It would not be practical. It is recommended when data volume is less than 16 TB.

• SAP HANA have very strict hardware design guidelines, so you cannot your own system architecture to install SAP HANA. • There is no way to migrate the data back to standard RDBMS from SAP HANA.

• There is no PITR (Point in time recovery) option available.

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