the mainframe data access & replication conundrum in today's heterogeneous it environment

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The Mainframe Data Access& Replication Conundrum

In Today's Heterogeneous IT Environment

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Mainframe Integration without Compromise

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Agenda

• Introduction to Treehouse Software• Today’s Situation• IT Objective• tcACCESS

• Data Integration• tcACCESS SQL Engine• tcACCESS Demo

• tcVISION• Data Replication• CDC Methods• Processing Stages• tcVISION Demo

• Summary

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Introduction to Treehouse Software

• Established in 1982• Mainframe system tools vendor• Leading ISV for Software AG

• 70% penetration in North American market• Consultants with 20+ years experience• More than 300 man years of experience

• Supporting all mainframe operating systems• Focus for the past 15+ years on data migration,

replication, and integration• Over 700 customers worldwide• 20 products• 30 employees

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Treehouse Customers

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Today’s Situation

• Heterogeneous IT environments

• Legacy applications

• High-availability information systems

• Data silos

• Increasing data volumes

• Exploding costs

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IT Objective

• Intelligent data integration

• Efficient data synchronization

• Cost effective solution

Enterprise-wide Data Management through:

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Enterprise Data Integration

• Bi-directional data-exchange across heterogeneous systems

• Direct data access across heterogeneous systems

• Data transformation for data analysis and exchange

tcACCESS Concepts

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Enterprise Data Integration

• Relational access to legacy data and applications

• Data federation – heterogeneous data views

• Integration of mainframe files and DBMS structures

• Data federation between mainframe and Windows/Open Systems data

tcACCESS Concepts

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tcACCESS SQL Engine

Host/PC & Host & Web Integration

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tcACCESS SQL Engine

• More than 90 SQL functions supported

• Operators (+, -, *, /, ||)

• Conditional Operators (>, <, =, BETWEEN, LIKE)

• Logic Operators (AND, OR)

• INNER and OUTER JOINS

• GROUP BY, ORDER BY

• Security may be applied (RACF, ACF/2, Top Secret)

• Stored Procedure Support

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tcACCESS SQL Engine

• Different data sources can be JOINed:SELECT IMS.NR, IMS.NAME, VSAM.ADDRESS FROM IMS, VSAM WHERE IMS.NR = VSAM.ID

• VIEWS can be created• Control Options available

(MAXIO, MAXROW, NOORDERBY, etc)

• Global SQL Exit available• Field Level Exits available

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tcACCESS Architecture

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Demo

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CDC Replication

• Different data formats

• Different data models

• Large data volumes

• Limited batch window

• Requirement for up-to-date information

• Moving/replicating data...

• as much as needed

• as little...

• as transparent...

• as flexible...

• as secure...

• ...AS POSSIBLE

The Problem: The Solution:

...with

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Data Latency

Change Data Capture

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Data volume

Change Data Capture

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Mainframe Change Data CaptureChange Data Capture

• Efficient transfer of entire databases

• Analysis for data consistancy

• Best for Initial Load prior to log processing

• Best for periodic mass data transfer

• One step data transfer

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Mainframe Change Data CaptureChange Data Capture

• Comparison of data snapshots

• Efficient transfer of changed data since last processing

• IMS/DB, DL/I, VSAM, DB/2, ADABAS, CA-IDMS, DATACOM, sequential files

• Flexible processing options (SORT etc.)

• Automatic creation of deltas by tcVISION

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Mainframe Change Data CaptureChange Data Capture

• Usage of the DBMS logging capabilities

• IMS/DB, VSAM, DB/2, DL/I, ADABAS, IDMS, DATACOM

• Transfer of changed data in scheduled time frame

• Best for batch window

• Best for processing right after logfile creation

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Mainframe Change Data CaptureChange Data Capture

• Realtime capture of changed data

• Changes directly obtained from DBMS

• CA-IDMS, IMS/DB, VSAM, DB/2, DATACOM, ADABAS

• Secure data storage even across DBMS restart

• Flexible propagation methods

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Stage 0:Data in internal raw format

Stage 1:Data in tcVISION format (before and after images)

Stage 2:Data normalized with structure definition

Staged Processing

Stage 3: Data in DML or Loader format

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Stage 0:Data in internal raw format

Stage 1:Data in tcVISION format (before and after images)

Stage 2:Data normalized with structure definition

Stage 3: Data in DML or Loader format

Staged Processing

Exit pointsavailable at every stage

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Demo

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Summary• Relational access to legacy

data and applications

• Data Federation – heterogeneous data views

• Change Data Processing

• Bi-Directional real time replication

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SummarytcVISION Architecture

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SummaryBi-directional data-integration and data-synchronization

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E-mail: sales@treehouse.com