IDUG-SyncsortSponsorshipMarch29,2018

VincentMannolini–SeniorAccountExecutive(O)8455356937(M)6034907662vmannolini@Syncsort.com

TrustedIndustryLeadershipFor“50”Years

Syncsort 2

800+Experienced&Talented

DataProfessionals

>7,000CustomersWorld-Wide

196850YearsofMarketLeadership

&Award-WinningCustomerSupport

86ofFortune100areCustomers

3xGrowthOrganic/Acquisition

ThegloballeaderinBigIrontoBigData

TheSyncsortSolutionSuiteDifferentiatedProductPortfolio&TechnicalExpertise

3 Syncsort

DataInfrastructureOptimization

DataAvailability

DataIntegration

DataQuality

Market-leadingdataqualitycapability

Best-in-classresourceutilizationandperformance,onpremise

orinthecloud

#1inhighavailabilityforIBMiandAIXPowerSystems

Industry-leadingmainframedataaccessandhighestperforming

ETL

• TrilliumSoftwareSystem• TrilliumQualityforBigData• TrilliumPrecise• TrilliumCloud• TrilliumGlobalLocator

• MFX®forz/OS• ZPSaverSuite• EZ-DB2• EZ-IDMS• DL/2• ZenSuite

• athene®• atheneSaaS®

• Distributed&z/OS

• MIMIXAvailability&DR• MIMIXMove• MIMIXShare• Quick-EDD/HA•  iTeraAvailability• Enforcive,Cilasoft,CSI

•  Ironstream®forSplunk•  Ironstream®TransactionTracing

• DMX&DMX-h• DMXChangeDataCapture

BigIrontoBigDataAfast-growingmarketsegmentcomposedofsolutionsthatoptimizetraditionaldatasystemsand

delivermission-criticaldatafromthesesystemstonext-generationanalyticenvironments.

Industry Leader in Mainframe and Distributed Software Products and Professional Services

DataReplicationTechnicalOverview

John Gay Sr. Manager, Sales Engineering Americas John.Gay@Syncsort.com 817-291-6440

INDUSTRYTRENDSANDPRACTICES

Today’sBusinessesHaveMultipleDatabases

 Multipledatabasesarethenorm–  Mergeroracquisition–  Choiceofmultipleappsordatabasesfor

bestofbreedsolutions–  Combinationoflegacyandnewdatabases–  Multi-organizationsupplychain

 ITinfrastructuresareheterogeneous–  Databaseplatforms–  Operatingsystems–  Hardware

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Does your organization rely on multiple databases?

Yes No I don't know.

83%

10% 8%

73% of those with multiple databases share data among databases

Does your organization share data between multiple databases?

Source: Vision Solutions 2017 State of Resilience Report

VariedBusinessandITGoalsforDataSharing

 OffloadingreportingtoprotectProductionSystemProvidedataformaintenance,backup,ortestingwithoutproductionimpactConsolidatingdataintoreal-timedatamartsSharingdatawithoutsideconsumersMigratingdatatonewdatabasesorapplicationversionsReplatformingdatabasestonewdatabaseoroperatingsystemplatforms

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Source: Vision Solutions 2017 State of Resilience Report

For what business purpose does your organization share data between databases?

Consolidating data from multiple sources into a single data warehouse

Performing Business Intelligence on data offloaded from the production

Reporting on data offloaded from the production data

Integrating data used by applications/databases selected for different

Synchronizing data between distributed applications

Dashboard generation

Testing on offloaded data

Feeding real time data to customer or partner facing applications

Running business processes on offloaded data

Master Data Management (MDM)

I don’t know

Other (please specify)

0% 10% 20% 30% 40% 50% 60% 70%

TRADITIONALMETHODSOFDATASHARING

TraditionalMethodsforSharingData

  Directnetworkaccess–  Reportingonproductionserversacrossthe

networkduringbusinesshours–  Issue:Negativelyimpactsnetworkanddatabase

performance–resultinginusercomplaints!

  Off-hoursreportsandextractions–  Runreportsoff-hoursor

performnightlyextractprocessestomovedatatoareportingserver–  Issue:Businessoperatesonagingdatauntilnextextraction–  Issue:Difficulttofindacceptabletimetoperformanextraction

  ETL(Extract-Transform-Load)Processes–  FTP/SCP/filetransferprocessesor

ManualscriptsorBackup/restoreorIn-housetools

–  Issue:Periodic,notreal-time,deliveryofdata–  Issue:Laborintensivetocreateprocessesandtools–  Issue:Expensivetodevelopandmaintain–  Issue:Pronetoerrors

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In-HouseETLScriptsandProcessesAreNotFree

 Upfrontdevelopmentcosts–  Developmentofcodetoperformdatabaseextraction,transformation,andload–  Additionalrequirementsforadditionalpairings,schemas,etc.

  Testsystemexpenses–  Hardwareandstorageresources–  Databaselicensesfortestsystems–  Add-onproducts,e.g.gateways

 Maintenancecosts–  Ongoingenhancementsforalteredschemas,additionalplatforms–  TestingnewdatabaseandOSreleases–  Crosstraininganddocumentationtoreduceturnoverrisk

  Lostopportunitycostsforotherinitiatives

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REAL-TIMEREPLICATIONOVERVIEW

MIMIXShareforEasy,AutomatedDataSharing

  Breaksdownbarriersbetweendatabases–  Sameordifferentdatabasemanagementsystems–  Sameordifferentoperatingsystems–  Physical,virtualorcloudplatforms–  Acrossanydistance

  Makesdatasharingeasy–  Replicatesdatabasechangesinrealtime–  Transformsandenhancesdataduringreplication–  Supportsleadingdatabaseandoperatingsystems–  Offersavarietyofreplicationarchitectures–  EasygraphicalUI–noprogrammingrequired!

  Quicklyreturnsyourinvestment–  Strongerdecisionmaking–  Greaterbusinessproductivity–  Abilitytochoosemorecost-effectiveinfrastructure–  FreesITtofocusonotherbusinessinitiatives

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ChangeDataCapture(CDC)forReal-TimeReplication

  ChangeDataCapture(CDC)capturesdatabasechangesimmediatelyandquicklyreplicatesthemtoanotherdatabase(s)

  Onlychangeddataisreplicatedtominimizebandwidthusage

  Automaticallyextracts,transformsandloadsdataintotargetdatabasewithoutmanualinterventionorscripting

  Ensureswriteorderconsistencyandguaranteeddelivery

  Ensuresdataintegritywithconflictresolutionandcollisionmonitoring

  Enablestrackingandauditingoftransactionsforcompliance

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Real-Time Replication

with Transformation

Change Data Capture (CDC)

Conflict Resolution, Collision Monitoring,

Tracking and Auditing

Source Database

Target Database

ReplacesManualProcesses

  Point&clickgraphicaluserinterface

  Singleviewofdataacrossdatabasesandoperatingsystems

  Simple,model-basedconfiguration

  Automaticallycreatestargettablesfromthesourcetabledefinition

  80+pre-built,click-and-godatatransformations

  TransformationscanbeaddedthroughJava-likescripting

 Noprogrammingrequired

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SupportsaBroadRangeofPlatforms

16 * Target only

Leading Operating Systems Leading Databases

•  IBM i

•  IBM AIX

•  HP-UX

•  Solaris

•  IBM Linux on Power

•  Linux SUSE Enterprise

•  Linux Red Hat Enterprise

•  Microsoft Windows, including Microsoft Azure

•  IBM DB2 for i

•  IBM DB2 for LUW

•  IBM Informix

•  Oracle

•  Oracle RAC

•  MySQL*

•  Microsoft SQL Server

•  Teradata*

•  Sybase

•  PostgreSQL*

SupportsaBroadRangeofPlatforms

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•  IBM DB2 for z (DMX-CDC)

•  IBM DB2 for i

•  IBM DB2 for LUW

•  IBM Informix

•  Oracle

•  Oracle RAC

•  Microsoft SQL Server

•  Sybase

High-LevelArchitecture

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Log-BasedDataCapture

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Did you know?

MIMIX Share can leverage published Log or Journal standards to identify and capture the change before copying to the MIMIX Share Queue.

The MIMIX Share Queue ensures that data integrity is maintained and zero data loss occurs in the event of a dropped connection during file transmission.

Queue

Source DBMS

Retrieve/Transform/Send

Apply

Changed Data

1

1 3

4

Log / Journal

Change Selector

2

1.  Use of transaction logs or triggers eliminates the need for invasive actions on the DBMS.

2.  Selective extracts from the logs and a defined queue space ensures data integrity.

3.  Transformation in many cases can be done off box to reduce impact to production.

4.  The apply process returns acknowledgment to queue to complete pseudo two-phase commit.

Target DBMS

FlexibleReplicationOptions

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One Way Two Way

Cascade

Bi-Directional Distribute

Consolidate

Choose a topology or combine them to

meet your data sharing needs

GuaranteesInformationAccuracy

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Ensures ongoing integrity §  Changes collected in queue on source §  Moved to target only after committed

on source §  Ensures write-order-consistency retained §  Queues retained until successfully applied §  No database table locking

Ensures failure integrity §  Automatically detects communications errors §  Automatically recovers the connection and

processes §  Alerts administrator §  No data is lost

SMTP Alerting

AccurateTracking&DataAuditing

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Audit Journal Mapping tracks all updates and changes §  Records

§  Before and after values for every column §  Type of transaction §  Type of sending DBMS §  Table name §  User name §  Transaction information

§  Records to flat file or to database table §  Can assist with SOX, HIPPA audit requirements

Detects and resolves conflicts §  Maintains data integrity

Model verification §  Validates date movement model

LetsYouShareExactlyWHATYouNeed

Filtersdeterminewhatdatagetsmoved–  Selectspecificcolumnandtable

–  Selectspecificrowsandtable

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LetsYouTransformtheDataExactlyHOWYouNeedTo

Transformsdataintousefulinformation  80+built-intransformationmethods  Fieldtransformations,suchas:

–  DECIMAL(5,2)–  nulltostring(ZIP_CODE,'00000')

  Tabletransformation,suchas:–  Columnmerging–  Columnsplitting–  Creatingderivedcolumns

  Customlookuptables  CreatecustomdatatransformationsusingpowerfulJavascriptinginterface

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MIMIXSHAREUSECASES

IBM System i DB2 Lawson M3 (Movex)

MS SQL Server

Query reports

Data Warehouse load

Real time CDC replication

with transformation

Reduce CPU and I/O overhead on production system

improve user response times

Many cost effective tools available on MS SQL server

platform for query reports

Data is already partially ‘scrubbed’ and available

for loading data warehouses and data marts without performance impact on

production system

Production System Offload Query System

UseCase:OffloadReportingfromProductionDatabase

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UseCase:CentralizedReporting

27

Casino 1

IBM System i DB2

Casino 2

IBM System i DB2

Casino 3

IBM System i DB2

Casino 4

IBM System i DB2

Casino 5

IBM System i DB2

Casino 6

IBM System i DB2

Single Data Warehouse Database Windows Cluster MS SQL Server

Customer loyalty Amounts paid Amounts won

Time at the table Time at the machine

Business intelligence

Real time CDC replication

with transformation

1. Customers enter new banking transactions on line.

They get captured in SQL Server

Microsoft SQL Server IBM System i DB2

On-Line Banking

replicates the transactions in

real time to DB2/400

3. A back-office batch application

processes incoming transactions and updates

data.

4. replicates the processed transactions back to SQL Server

in real time.

1

2

3

4

5. Customers view processed transactions

on-line

5

Bi-directional replication

UseCaseApplicationIntegration

28

Replicated data is merged into a single, consolidated reporting database in the cloud (AWS, Azure, etc.)

3

UseCase:ReportingintheCloud

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End users enter data into their

local applications.

Target

MIMIX Share captures, transforms,

and replicates database changes in

real-time.

Business Intelligence apps and reporting tools access the

consolidated information from the cloud-based database.

1

2

4

Source

UseCase:DatabaseMigration

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IBMiDB2fori

JDE(standard)

OldSystem

IBMiDB2fori

JDE(Unicode)

NewSystem

Manufacturing Company

Real time CDC replication

with transformation

UseCase:DatabaseReplatforming

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IBMiDB2

OldSystem

SunOracleRAC

NewSystem

Large Insurance Company

Two-way Active-Passive replication to enable

application server switching

Near-zero downtime for cutover to new

systems

Transformation between different OS and database

platforms Users are moved to new server in phases over a

period of time

UseCase:GradualDatabaseReplatforming

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IBMiDB2

OldSystem

WindowsSQLServer

NewSystem

America II Corp

Active-Active replication eliminated need for hard

cutover and enabled partners to move back and

forth between systems

True zero downtime for migration to new

systems

Transformation between different OS and database platforms with completely

different schemas

100s of partners moved to new server after training

nd at their own pace

WHATTOLOOKFORWITHCDCREPLICATION

WhyMIMIXShare?

1.   SuperiorDataIntegrity–  ZeroDataLossEVER–  AutonomicRecovery

•  Network•  Server•  Data

2.   SuperiorAdministration–  GraphicalInterface–  Single-StepPromotiontoProduction–  ReplicationSchemaLanguage(RSL)–  ModelBased

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WhyMIMIXShare?

3.   SuperiorPerformance–  FastThroughput–  Off-BoxOption

4.   SuperiorMonitoring–  Client,Web-based,Command-line–  Network,Server,Database,Transactions–  ProactiveSMTPE-MailAlerts

5.   IntegrationwithOtherProcesses–  SharingofJournals/Logs–  CoupledRole-Swap–  Downstreamdataprocessing

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36

ThankYou!

37

Tak Bedankt

Takk

Kiitos Merci Danke Grazie

Dziękuję Multumesc Gracias Tack Hvala

감사합니다 謝謝您 Благодаря Thank You

www.visionsolutions.com

Terima Kasih Köszönet

MappingColumns

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column mappings

Customer number Customer name

Numeric (10)

Customer address line 1 Customer address line 2

Alpha-numeric (10) Alpha-numeric (25) Alpha-numeric (25)

Customer address line 3 Customer address line 4

Alpha-numeric (25)

Customer telephone Customer credit limit

Alpha-numeric (25)

Numeric (10) Numeric (10,2)

Customer address line 5 Alpha-numeric (25)

Column Name Data Type

Target Server

Database Server MS SQL Server

customer_master (SQL table)

CUNUM

CUNAM

Numeric (10)

CUAD1 CUAD2

Alpha-numeric (20) Alpha-numeric (25) Alpha-numeric (25)

CUAD3 CUAD4

Alpha-numeric (25)

CUTEL

CUCLM

Alpha-numeric (25) Numeric (10)

Numeric (10,2)

Column Name Data Type

Source Server

Database Server DB2

CUSTPF

table mapping

HowDoesYourBusinessNeedtoMoveData?

  Enablingqueries,reports,businessintelligenceoranalyticswithoutproductionimpact?

  Populatingcentralizeddatabases,datamartsordatawarehouses?

  Feedingreal-timedatatoemployees,customersorpartners?

  Keepingdatafromsiloeddatabasesinsync?

  Reducingtheimpactofdatabasemaintenance,backuportesting?

 Movingdatatonewdatabases?

  Consolidatingdatabases?

  Replatformingtonewdatabaseoroperatingsystems?

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AdditionalUseCases

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ERP SYSTEM

Customer Orders Payment Details

Product Catalogue Price List

eCOMMERCE & WEB PORTALS

DR / BACKUP

DATA EXCHANGE WITH OUTSIDE VENDOR

(FLAT FILE)

Outside Vendor

TEST & AUDIT ENVIRONMENT

MIMIXShareTransformsBusiness

  Breaksdownbarriersbetweendatabases–  SameordifferentDBMSorOS–  Physical,virtualorcloudplatforms–  Acrossanydistance

  Makesdatasharingeasy–  Replicatesdatabasechangesinrealtime–  Transformsandenhancesdataduringreplication–  EasygraphicalUI–noprogrammingrequired!

  Quicklyreturnsyourinvestment–  Strongerdecisionmaking–  Greaterbusinessproductivity–  Abilitytochoosemorecost-effectiveinfrastructure–  FreesITstafftofocusonotherinitiatives

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ConnectwithVision!

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Website:visionsolutions.com

Twitter:twitter.com/VSI_Power

@VSI_Power

Facebook:facebook.com/VisionSolutionsInc

YouTube:youtube.com/c/VisionSolutionsInc

LinkedIn:linkedin.com/company/vision-solutions

Blog:http://blog.visionsolutions.com

HowtoLearnMore

 Readcasestudies

 Downloadawhitepaper

 ReadtheMIMIXSharetechbrief

 Watchproductsdemoonourwebsite

 Listentoanon-demandwebcast

 ConnectwithVision’ssocialmediasites

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