Comparison of Replication methods in SAP Hana

Comparison of Replication Methods:

Capability                Trigger-Based                       ETC-based Replicates                   log-based Replication

Replication              (Data services 4.0-SP2)         (Sybase Replication)                     (SLT Replication)

Release                    SAP R/3 4.6C-SAP                 ERP 4.6c – SAPERP 6.0                SAP ERP 6.0 (only it Unicode)

coverage                  ERP 6.0 (EDHP06)

All other ABAP –based SAP applications (Basis 4-6c-No702)

Unicode/ Non-Unicode      Yes                                             YES                                        Unicode only

MDMP, Partial (if the table contains only ASCLL Characters or Languages key included)

Transparent                      Yes                                         Yes                                                         YES

Tables

Cluster 4pool                    YES                                        Yes                                                         NO

Tables

Non – SAP          Yes(For SAP suspected)                      Yes                                         Yes, but not in the scope

DBS only: Informix out of maintainable therefore not supported DBU and Sybase ADE Sybase ASE not yet corned planned with sp sole.

Capability                        trigger                                    ETL                                                      

log Compressed values    yes                                       yes                                           DB2 (9.1.9.5,9.7)

Row compression DB Table  yes                                   yes                                           DB2 9.7 oly (no support for 9.1 or 9.5)

DB support (Sour vibe)                All SAP supported DB s, ind. ASE                    All SAP supported DBS. incl. ASE and others        

DB 2 LUW/UDB See PAM for full list         only (no MAXD B Support) OS support (source side)            

All SAP supported             OS                                          NO                                           YES

Hotly system support      Multiple source                Multiple source                  single-source systems to multiple systems to  single

SAP HANA instances      SAP HANA instance core source system can be connected to one SAP HANA schema only

Transactional integrity        Not covered yet               No                                          NO (planned with sp SD4)

Workload balancing               Yes                                Yes                                         Yes (parallelization of replication)

Real-time and /or              Real-time and scheduled                                     Real-time scheduled replication scheduled cor table                                                         

(by logical level work Units) Initial load & data initial load + delta replication data replication for replication (for replication (always relevant tables table based needs incl. repository delta information info for all tables !)

through timestamp column or chough delta enabled extractors) Transformation                              

support dashboard                        via data service own                                                             Performer dash capabilities                                                                                         

management console            board(load progress or through the into and throughput gration with SAP structure)

solution manager Access to trouble                            yes, via data services shooting future own management console or through the integration with SAP solution MANAGER    

Integrating SAP In-Memory Appliance (SAP HANA) into your system landscape:

SAP HANA Overview:

SAP HANA Installations & updates:

• The pre-packaged solution is delivered as an installed and pre-configured system to the customer site
• Built-in Tools for life cycle management securing optimization and operation
• Best practices in tasks, concepts, and procedures necessary for the ongoing operation

Architect &   Installation  Administration             update        Backup & landscape         & monitoring        & patching   recovery  

SAP HANA Combines software & hardware:

In-memory Computing engine (s/f) + Pre-installed system (H/W). Both are designed by Hp, IBM, Fujitsu, CISCO, and DELL.  

SAP SOFTWARE COMPONENT ARCHITECHTEORE:

The SAP HANA appliance software from a deployment point of view: A well-defined and validated stack of HW & SW components

• SAP HANA 1.0 SPS 02
• SAP HANA database
• SAP HANA database clients
• SAP HANA stucco (p2 repository)
• Sybase replication server
• SAP HANA LOAD controller
• SAP Host Agent
• LM structure files
• SAP CAR
• OS configuration & uses
• SL TOOL set 1.0 SPS D2
• Software 1.0 update manager for SAP HANA
• SAP JVM

Scale-out:

Multiple nodes utilizing shared files for workload distribution

Disaster Tolerance Redundant Hard wore:

Fiber node:

Cold stand by the node will table over for downed nodes

• SIZING HANA:
• RAM RAM = Source data footprint * 2/5
• Disk persistence = 4* RAM

Disk log = 1* RAM

CUP 0.2 CUP cores / active user

Memory sizing: static data

Memory requirements for static data are derived from the database footprint of the corresponding tables of the source database system Database footprint in source system must be determined using database specific catalog information (Eg: in Order: dba _segments: in DB2: syscat tables) Database specific scripts and more details on how to determine the database footprint can be found in not 1609322 Average compressing factor database table size: SAP HANA memory = 5:1 Note that this compressed factor refers to uncompressed database tables, and space for database indexes is to exclude.

Memory sizing: runtime objects:

Additional memory required for objects that are created dynamically

• When loading new data
• When exciting queries

We recommend to reserve as much memory for dynamic objects as for static objects:

So the total RAM is

DISK SIZING:

’cuP' sizing:

Sizing approach similar t user based CUP sizing of BW & BWA Maximize query through  by multi-user scenarios with queries of different delivered content, 10-20M records