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Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 1


SAP In-Memory Computing, ein Wendepunkt ? Vertrauen in Oracle Technologie.

Stefan Menschel Master Principal PreSales Consultant Business Unit Server Technology - Datenbank Oracle Deutschland B.V. & Co. KG


Safe Harbor Statement

The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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Market Trend

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Databases Random Access Memory

Flash Storage

Central Processing Unit

Software Hardware


Data, Data, Data, …… Data are IN §  Data Analysis is becoming important in the foreground §  Databases are perceived at all levels of the IT §  Database specialists are needed §  Database-driven developers have a future §  Database Architects / good DBAs have a future

à In-Memory Computing à Big Data Databases are IN

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The Database Market is dynamic Databases are IN

Oracle DB TimesTen

MySQL

MariaDB

DB2 RDB

MemSQL

Couchbase

Oracle noSQL

Vertica

ExaSol

SQLServer

Teradata

BerkleyDB

Sybase

SAP Hana

SolidDB Basko

Mongo DB Postgres

Informix Aerospike

Datastax

Voldemort

HBase

Cassandra

Neo4J

.... and many more

AmazonRDS

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Essbase


Infrastructure Conventional Systems Standardization

§  Database Server - individual Manufacturer - Operating System xy - Virtualization - Patch Level xy §  complex Deployment

§  Maintenance §  Finger-Pointing §  High Availability / Scalability

à more complex §  Risk (Patching) §  many different tools for

Monitoring & Administration

§  Storage Array - individual Manufacturer - Operating System xy - Patchlevel xy

§  Host Bus Adapter - individual Manufacturer - Firmware xy

§  FC-Switch - individual Manufacturer - Firmware xy

? à Contradiction !

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UNIQUE SYSTEM


Oracle Engineered Systems

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Exadata Supercluster

Exalogic Database Appliance

ODBLRA


Oracle Engineered Systems Advantage : Standardization

Reduce IT Costs §  faster Deployment §  speed Business Value §  less Operations §  less Mainentance §  less Finger-Pointing §  High Availability

Scalability included §  less Risk

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Oracle Engineered Systems Advantage : Performance out of the box

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Exadata, first Turbo for your Data.


SAP In-Memory Computing ein Wendepunkt ?

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SAP HANA is a completely re-imagined platform for real-time business.

SAP Business Suite on HANA, Change the Game.

SAP HANA is Real Real Time Computing

Fast, slim, more smartly with SAP in-MEMORY Computing are you the competition always a step ahead

SAP HANA accelerates analytics and applications on a single, in-memory platform. Get ready for real-time business

"We have already changed the game and we are moving onto the next frontier.“ SAP CTO Vishal Sikka 2013-09-22


In-Memory Computing (In-Memory Data Management IMDM)

Why ?

§  Growth of Databases §  Big Data

§  Data Silos (OLTP+OLAP)

§  MultiCore CPU §  RAM

§  SSD

Reality §  Real Time Computing

§  Analytics §  Performance à Speed

§  Simplify IT

Demand

„Everything must go fast. We live in an NOW economy. “ Gartner 2002

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In-Memory Data Management

SAP HANA = Database ?

YES

HANA is an application platform, not a database. http://www.saphana.com/community/blogs/blog/2013/07/18/the-top-10-sap-hana-myths-spread-by-other-vendors

YES

NO

What is it ?


SAP HANA (Database) – Central Part of SAP Real Time Data Platform

SAP HANA Database

SAP Sybase ASE (Database)

SAP Sybase IQ (Database)

SAP Sybase ESP (Event Sream Processor)

SAP Sybase SQLA (SQL Anywhere)

SAP Real Time Data Platform

SAP Netweaver HANA App Server

SAP Business Suite

SAP Business Warehouse

SAP Big Data Applications

SAP Analytics

SAP Mobile

Custom Apps

SAP HANA Appliance

Sybase ASE run on Infrastructure

Sybase IQ run on Infrastructure


In-Memory Data Management What is different ?

Last Name

First Name

Email Phone# Street Address

Last Name

First Name

Email

Phone#

Street Address

IMDM (new) Column Based (Column Store)

DISC

RAM RAM

+ INSERT new record + UDATE existing record - useless reads

+ read only relevant data + high compression - INSERT / UPDATE complex – Persistence on Disc

Traditional Row Based (Row-Store)


Func

tiona

lity

Requirements of a Database Not Everything is about Performance !

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Func

tiona

lity

SAP HANA Specialized Database for Analytics

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Query Performance based

on high compressed In-Memory

Column Store

Missing Functionalitys

in SAP HANA


Multiple Changes to go to SAP HANA The Requirements for more Performance

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new Database other dedicated Database Server other dedicated Storage System

Application(s) powered by SAP HANA

new Application(s) SAP Netweaver BI powered by SAP HANA SAP Business Suite powered by SAP HANA Appl. Accelerator(s) for SAP HANA

other Backup / Restore Functionalities

other HA Features other Scalability Features

... and all in 1 Step


SAP HANA Fundamentals – Load Operations

A1

B1

C1

D1

E1

A2

B2

C2

D2

E2

A3

B3

C3

D3

E3

A4

B4

C4

D4

E4

A5

B5

C5

D5

E5

A6

B6

C6

D6

E6

Oracle DB

A1

A2

A3

A4

A5

A6

SAP HANA Disk and SSD

B1

B2

B3

B4

B5

B6

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

Initial Load

A1

B1

C1

D1

E1

A2

B2

C2

D2

E2

A3

B3

C3

D3

E3

A4

B4

C4

D4

E4

A5

B5

C5

D5

E5

A6

B6

C6

D6

E6

SAP Business Objects Data Services SAP Landscape Transformation Services

Permanent Store Column Store on Disk

®


SAP HANA Fundamentals – Read Operations

SAP HANA

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

SELECT col1, col2 FROM tab WHERE col1 = A4 AND col2 = B3;

A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

B5

B6

load 100% of the column in memory on demand

MainStore

A1

A2

A3

A4

A5

A6

PK – Index

B1

B2

B3

B4

B5

B6


SAP HANA Fundamentals – Write Operations

SAP HANA

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

B5

B6

UPDATE tab SET col1 = ‘AX‘ WHERE col1 = A5;

Update to INSERT into DeltaStore (INSERT only Mode)

DeltaStore

AX

write DELTA to

COMMIT Log on SSD

A5

Read Operations


SAP HANA Fundamentals – Merge Process

SAP HANA

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

A1

A2

A3

A4

A6

B1

B2

B3

B4

B5

B6

Asynchronous Single Column Merge Operation DeltaStore à MainStore

AX

Lock on DeltaStore

A1

A2

A3

A4

A X

A6

Copy of MainStore

new empty

DeltaStore

More CPU ... Double RAM of MainStore ... Savepoint creates Disk I/O

write Savepoint (complete MainStorage) for Persistence on Disk

Rebuild Index

I/O

Lock on MainStore


SAP HANA

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

A1

A2

A3

A4

A6

B1

B2

B3

B4

B5

B6

AX

A1

A2

A3

A4

AX

A6

Exchange MainStore with new „MainStore“

X X

new DeltaStore

MainStore DeltaStore

Copy of Main Store New DeltaStore

SELECT col1, col2 FROM tab WHERE col1 = AX AND col2 = XX;

SAP HANA Fundamentals – Consequences

Lower Performance

for Read + Write Operations

Per

form

ance

Read from


SAP HANA Fundamentals – Passiv Data

SAP HANA

C1

C2

C3

C4

C5

C6

D1

D2

D3

D4

D5

D6

E1

E2

E3

E4

E5

E6

A1

A2

A3

A4

AX

B1

B2

B3

B4

other SAP Databases run on other Infrastructure

Sybase IQ

Sybase ASE

Persistence of Nearline Storage for Passiv Data

B5

B6

A5

A6

B5

B6

A5

A6

X X

Passiv Data

Aktiv Data


In-Memory Database Power Failure : Consequence

User

Application Server

HANA DB Server + HANA Storage

SAP ERP

User

Application Server


Server Side Failover

1:1 System Replication


Shared Nothing Cluster Distributed SAP HANA System

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DB Partition 1

Worker Node

Index Server Statistic Server Name Server (Row Store)

Column Store SAP HANA Studio

HD Flash

data01 log01 Primary Data

Replica

Shared Filesystem - GPFS

SAP HANA Database

Node 1

DB Partition 2

Worker Node

Index Server Statistic Server Column Store

Backup Name Server

HD Flash

data02 log02

Node 2

DB Partition 3

Worker Node

Index Server Statistic Server Column Store

HD Flash

data03 log03

Node 3

Standby Node

Index Server Statistic Server

HD Flash

Node 4

®

not supported for SAP Business Suite on HANA

(SAP Note 1825774)


Source : SAP HANA Documentation: http://help.sap.com/hana_appliance/

Fact : HANA Cluster = no HA Solution !

Shared Nothing Cluster Add a new Node to the Cluster


Backup & Recovery Not Enterprise Ready Full Backup Only

- no support for incremental backups No Granularity Beyond Data Files and Logs - no support to backup and recover database objects No Integrated Tape Backup / Limited Media Management Support - backups only to a specified disk destination Poor Design Around Backup Catalog – Significant Data Loss Exposure - Backup Catalog is located inside the HANA database itself à database gets corrupted / destroyed, all relevant backup information will be lost Inefficient Recovery Process - database recovery process, once started, cannot be interrupted Lacking Several Enterprise-level Backup & Recovery Features - missing are: backup encryption, backup compression, validation of backup & restore without actually doing the backup & restore, block recovery, incrementally updated backups, optimized backups, parallel backup channels, media management integration

§  Block Corruptions §  Logical Errors


Multivendor for HANA Appliance

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SAP HANA Appliance à “special optimization” at the system level à different HANA Appliances

IBM x3690, x3950 X5 HP Proliant BL680c G7, DL980, DL580 Dell PowerEdge R910 Cisco UCS B440 M2, C460 M2, C260 M2 Fujitsu RX600 S6, RX900 Hitachi CB2000, Unified Compute Platform (UCP) NEC Express A1040a, A1080a VCE Specialized Vblock for SAP HANA Huawei Tecal RH5885 V2 for SAP HANA

9 Server Brands – 18 Server Models

Source: “Validated SAP Partner Hardware”, SAP HANA Hardware Specifications & Product Availability Matrix (PAM)

High Complex High Risk Complex Patching

NetApp FAS3240 HP X9300 Network Storage System HP P6500 Enterprise Virtual Array NEC Storage M500 Viridient FlashMax IBM DS3524 Hitachi AMS 2100 Fusion I/O Dell Compellent SC8000 EMC VNX 5000 EMC VNX 7000 Netapp

9 Storage Brands – 11 Storage Models

IBM GPFS ext3 XFS

Three File Systems


Multivendor - Consequences Lacks end-to-end manageability à multiple tools & support from different HW vendors

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Different Management Solutions of SAP HANA Appliances


Architecture Limitations

with HANA SP 4 (October 2012) §  no system consolidation possible (note 1661202) §  one HANA appliance (“system” or “cluster”) can only accommodate one HANA database (SID).

For test systems, multiple databases on one appliance are supported provided that it is installed by a certified SAP consultant

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Consequence HANA based Datacenter (Production Environment)

User

Application Server


SAP Netweaver BI

User

Application Server


SAP ERP

User

Application Server


SAP HR

...


DSAG Blaupause Nr. 25 in 2013 „Die technische Installation von SAP HANA dauerte lediglich zwei Monate. Und dann wurde es doch noch etwas aufwendiger. ... Da muss alles fein aufeinander abgestimmt werden. Der Replikationsmechanismus, also wie die ERP Daten möglichst schnell und reibungslos nach SAP HANA kommen, wie lange das dauert etc., all das muss geprüft und getestet werden. Dafür sind dann auch wirklich die SAP Experten vor Ort gefragt...“ Marcus Gerke, CIO der TRILUX GmbH & Co. KG und Mitglied des DSAG CIO Beirats

Experience from German Customer


Other Customer Experience with

SAP HANA

„As to the re-implementation, I have to disagree with you. I was on a project to migrate a SAP app (whose name cannot be mentioned here) to HANA. Admittedly 30% of the functionality runs at least 10X times faster out of the box. However for the rest 70%, after almost a whole year's efforts from both SAP and ourselves in re-writing and re-testing, we eventually achieved a like-for-like performance on a much more modern hardware platform. My point here is there are certain workloads running much better in row-oriented DBMS, and you do have to optimize the codes when you migrate to a full column oriented DBMS.“ Source : http://www.saphana.com/community/blogs/blog/2013/10/08/why-wait-for-100x-performance 2013-10-30 „Also, SAP HANA is not pre-optimized to support non-SAP applications, which requires significant application re-engineering on the part of enterprise IT groups.“ Source : http://wikibon.org/wiki/v/Primer_on_SAP_HANA 2013-10-31

Application Re-Implementation

„In TAMKO's case, the HANA RDS didn't include the development of a security model, so the company had to bring in a security consultant at additional cost.“ Source : http://www.infoworld.com/d/applications/early-sap-hana-customers-separate-reality-the-hype-205262?page=0,1 2013-10-31

Security + Costs

Die Sicherung und Wiederherstellung einzelner Datenbank Objekte ist nicht möglich. Um die SAP HANA Datenbank wiederherzustellen, muss die Datenbank komplett heruntergefahren werden. Source : http://jk-netzwelt.de/?p=5924 2013-10-31

Backup/Recovery

Performance Factor 10x Only Complete Restore need Code Optimizations less Security


SAP HANA What does it mean ?

§  optimized solution for analytics §  improved BW Queries §  improved data load processes §  new reporting functions

pro §  new additional expensive SAP License §  high implementation costs §  high risk – complete new database §  complex Data Replication

(HANA as Accelerator) §  Investments cannot be otherwise used §  new operational processes §  more complex §  frequent patching cycle §  operating system only SUSE Linux §  less database functionalitys

(Backup / Recovery, Security, HA, Scalability, ...) §  several monitoring / admin tools §  re-writing program codes

cons


SAP Commitment Next Innovations

Open Choice and Full Support to Customers SAP remains committed to support its customers’ choice of database technologies and vendors. SAP will continue to provide innovation for all databases supported and work with its database partners to support these innovations, which may include in-memory optimizations.

http://www36.sap.com/corporate-en/news.epx?PressID=20221

SAP Business Suite remains open to other database technologies and vendors and only one version of SAP Business Suite goes forward without disruption. Innovations in the SAP Business Suite, such as push down of data centric processing logic from the application server to database tier via stored procedures would be made available to other databases too making them perform better too.

http://www.saphana.com/community/blogs/blog/2013/01/10/a-promise-delivered-sap-business-suite-is-now-powered-by-hana

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Video Prof. Dr. H.C. Hasso Plattner SAPPHIRE Orlando 2013

(2 minutes)


UST – TRUST – TRUST – TRUST – TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST - TRU TRUST – TRUST – TRUST – TRUST – TRU

RDBMS - Market Leader

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Vertrauen in Oracle


Oracle Technology Engineered to Work Together

Oracle DB Oracle Infrastructure

Oracle Database §  Oracle 11g §  Oracle 12c

- Multitenant Database - In-Memory Columnar Technology - Heat Map - Automatic Data Optimization

Oracle Infrastructure §  Oracle Engineered Systems

- Exadata Database Machine - Exalogic Elastic Cloud - Supercluster - Database Appliance - Exalytics

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Oracle RDBMS Technology Innovation

§  Client Server Architektur

§  Multiversion Concurrency Control (MVCC)

§  Oracle Parallel Server §  PL/SQL §  Row – Level - Locking

Release 4 (1984)

Release 5 (1985)

Release 6 (1988)

§  Foreign Key Constraints §  Stored Procedures §  Trigger §  Datatype LONG

Release 7 (1992)

§  Cost Based Optimizer §  Transportable Tablespaces §  Unicode UTF 8 §  Datatype CLOB, BLOB §  Function Based Index §  Online Reorg Index §  Index org. Tables IOT

Release 8 (1997)

§  Online Reorg Table §  Undo Segment §  Partitioning §  Flashback §  Bitmap Index §  Real Application Clusters

Release 9 (2001)

§  Recycle Bin §  ASM (Storage Volume Manager) §  ADDM (Diagnostic Monitor) §  SQL Profile

Release 10 (2003)

§  Compression §  Datatype Secure Files §  Deferred Segments

Release 11 (2007)

Performance - Flexibility – Availability - Scalability - Security - Manageability Best in


Oracle RDBMS The Next Innovation

"Oracle Database 12.1c will be a "columnar, compressed, high-speed, in-memory database." Ellison said during Oracle's quarterly earnings call Thursday "One reason I was confident SAP HANA could never compete with Oracle was because of 12.1c."

Source : June 20 , 2013 http://www.computerworld.com/s/article/9240232/Oracle_s_Ellison_spills_beans_on_upcoming_SAP_HANA_competitor_and_Database_12c_plans

Release 12 (2013)


Oracle Database 12c In-Memory Option

§ Leading edge In-Memory technology -  seamlessly integrated into Oracle Database

§ Delivers Extreme Performance for -  Analytics and Ad-Hoc reporting on live data -  Enterprise OLTP and Data Warehousing -  Scale-up and Scale-out

§ Trivial to Deploy for All Applications and Customers

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§  BOTH row and column in-Memory formats for same table

§  simultaneously active and transactionally consistent

§  analytics & reporting use NEW column format

§  OLTP uses row format

Breakthrough : Dual Format Oracle In-Memory Database

Column Format

Memory

Row Format

Memory

Analytics OLTP Sales Sales

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Oracle 12c : Store Data in Both Formats Simultaneously

Optimizing Transactions and Query Performance Row Format Databases vs. Column Format Databases

Row § OLTP runs best on row format

–  Operates on few rows, many columns

Column § Analytics runs best on column format

–  Operates on few columns, many rows

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Func

tiona

lity

Oracle Database Multi-Purpose Database

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In-Memory Column Store in Oracle 12.1


Why Considering Engineered Systems for SAP Safe Transition to a New Era

§  runs SAP unchanged

§  eliminate systems integration trial-and-error

§  better performance out-of-the-box

§  reduce vendors to Oracle and SAP

§  best support (identical hw in Walldorf)

§  fast and online migration

§  apply existing personnel, skills, Oracle licenses

§  less administration, simpler patching, greater uptime

§  consolidate platforms and databases, reduce power and cooling

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High Integrated Products for Extreme Performance

+


®

Simplify I.T. Engineered Systems

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Documents

1 Copyright © 2013, Oracle and/or its affiliates. All ... slim, more smartly ... Update to INSERT into DeltaStore (INSERT only Mode) DeltaStore A X ... Sybase IQ Sybase ASE Persistence