2. Team Members
GARIMA CHAURASIA
GEETANJALI RANA
ABHISHEK AGRAWAL
Under Guidance Of
Professor LOU THOMPSON
Professor KASHIF SAEED
3. Develop basic understanding of “What is SAP HANA”
How SAP HANA is different from traditional databases
SAP HANA evolution and architecture
Use SAP HANA Studio for data modeling and reporting
Overview of other objects that can be created in SAP HANA
Session Objectives
4. What is SAP HANA?
RDBMS
Application Server
XS-Engine
RDBMS
Application Server
XS-Engine
HANAAppliance
Primarily
5. What is OLTP & OLAP?
Name Expense Type Date Amount
John Flight 1st Jan $400
Max Hotel 5th Jan $200
John Hotel 8th Jan $100
Max Flight 8th Jan $500
John Hotel 15th Jan $300
Max Hotel 20th Jan $150
Expense Report on Paper
6. What is OLTP & OLAP
Employee ID Employee Name
E1 John
E2 Max
Transaction Data
OLTP System
Name Expense
Type
Date Amount
John Flight 1st Jan $400
Max Hotel 5th Jan $200
John Hotel 8th Jan $100
Max Flight 8th Jan $500
John Hotel 15th Jan $300
Max Hotel 20th Jan $150
Master Data
Expense ID Expense Description
F Flight
H Hotel
7. What is OLTP & OLAP
Name Expense
Type
Date Amount
John Flight 1st Jan $400
Max Hotel 5th Jan $200
John Hotel 8th Jan $100
Max Flight 8th Jan $500
John Flight 15th Jan $300
Max Hotel 20th Jan $150
Name Expense
Type
Month Amount
John Flight Jan $700
John Hotel Jan $100
Max Flight Jan $500
Max Hotel Jan $350
OLAP (Summarized)
OLAP System
OLTP (Detailed)
8. What is OLTP & OLAP
Name Expense Type Month Amount
John Flight Jan $700
John Hotel Jan $100
Max Flight Jan $500
Max Hotel Jan $350
Report: Total January Expense
OLAP System
$1650
9. What is OLTP & OLAP
OLAP SystemsOLTP Systems
SAP ERP / SAP CRM SAP BDW
SAP HANA
(Single system for both OLTP and OLAP)
10. SAP HANA Evolution
SAP
HANA
SAP
Business
Warehouse
powered
by HANA
SAP
Business
Suite
powered
by HANA
SAP
Simple
Finance
powered
by HANA
SAP
S/4
HANA
In-memory
Platform
Real-time
analysis
Real-time
reporting
Real-time
business
OLAP and
OLTP
together
SAP HANA
Enterprise
cloud
Real-time
business
OLAP and
OLTP
together
SAP HANA
Enterprise
cloud
Simplified
data Model
New User
Experience
Advanced
Professing
Choice of
deployment
(Cloud On-
Premise)
2011 2012 2013 2014 2015
11. Traditional v/s HANAArchitecture
Presentation Layer
Application Layer
Traditional
Architecture
Presentation Layer
SAP HANA
Architecture
Traditional
Database
Management
System
HANA
Database
Management
System
Application
Layer (XS)
12. Traditional Data Processing
Presentation Layer
Application Layer
Traditional Database Management System
Request
Result
Response
Total Sales
2015
Business
Logic
SQL Query
Processing
13. SAP HANA Data Processing
HANA DATABASE
Application Layer (XS) Control Logic
Presentation Layer
Request Response
Total Sales
2015
16. Inception of SAP HANA
SAP HANA
BWAccelerator In-Memory
Appliance
TREX – Text Retrieval and
Information Extraction
MAX DB
Relational
Database
P*TIME
OLTP
In-Memory DB
In-Memory
Columnar Storage
In-Memory
Row Store
HANA DB
Persistence
17. No Aggregate Tables
Partitioning
Row and Column Store
Compression
High Capacity RAM
Multi CPUs
Multi Core CPUs
Massive Parallel
Processing
Hardware & Software Innovations
Software Hardware
23. Traditional Storage Technique
Write Intensive
Query Performance Slower
Occupies more space
Aggregated Serially
Configuration Tables
SAP HANAApproach
Read Intensive
Query Performance Faster
Occupies less space
Aggregated in real time
Master and Transaction Tables
Row and Column Store
Row Store Column Store
SAP HANA
can store data in
Row & Column Format
29. Column Storage In HANA
Dictionary for
Student Name
Attribute Vector for
Student Name
Distinct
Values
All
Values
Sample
Data
30. Data Retrieval - Column Storage
Dictionary AV
Distinct Values All Values
Sample Data
Dictionary
AVDictionary
AV
SELECT all records where student name = Nikhil
Nikhil
Nikhil
S1
S5
M
M
31. HANAArchitecture
Business Applications (ERP,CRM, BW OR HANAApplications)
Transaction
Manager
Authorization
Manager
Metadata
Manager
Persistency Layer
Session Manager
Page Management Logger
Disk StorageData Volumes Transaction Log Volumes
RAM-Relational EngineIn Memory Row Store
SQLScript MDXSQL …
Calculation Engine
Execution Engine
In Memory Column Store
Planning Engine
32. Presentation
Layer
Memory
Persistency
Layer
Disk
Storage
A = 10 B=20
A = 15 B=25
A = 10 B=20
A = 10 B=20
A = 10 B=20
SQL SQL
Persist Persist
Savepoint Every 5 MinsSavepoint Every 5 mins
A = 15 B=25
A = 15 B=25
A = 15 B=25
Current
State
Modified
State
Persist
State
HANAArchitecture Flow
33. Presentation
Layer
Memory
Persistency
Layer
Disk
Storage
A = 10 B=20
A = 15 B=25
A = 10 B=20
A = 10 B=20
A = 10 B=20
SQL SQL
Persist Persist
Savepoint Every 5 MinsSavepoint Every 5 mins
A = 15 B=25
A = 15 B=25
A = 15 B=25
Current
State
Modified
State
Persist
State
HANAArchitecture Flow
