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All about Oracle Golden Gate by Udaya Kumar Pyla

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Overview of OGG - Oracle Golden Gate

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All about Oracle Golden Gate by Udaya Kumar Pyla

  1. 1. Copyright © 2017 Tech Mahindra. All rights reserved. Oracle Golden Gate By Uday Kumar P
  2. 2. Copyright © 2017 Tech Mahindra. All rights reserved.  Introduction & Overview of Golden Gate  Golden Gate components  Logical Architecture  Supported Topologies Agenda
  3. 3. Copyright © 2017 Tech Mahindra. All rights reserved. Introduction & Overview of Golden Gate What is Oracle Golden Gate ? Oracle’s Strategic Data Replication solution Delivers Real-time access of Real-time information Improves the availability, reliability and performance of critical data across the enterprise
  4. 4. Copyright © 2017 Tech Mahindra. All rights reserved.  Enables the exchange and manipulation of data at transaction level  Available across multiple, heterogeneous platforms across the enterprise  Modular architecture gives flexibility to extract and replicate selected data records, transactional changes and changes to DDL across a variety of topologies. Introduction & Overview of Golden Gate Cont.. What does Golden Gate do ?
  5. 5. Copyright © 2017 Tech Mahindra. All rights reserved. Golden Gate Components  Manager  Extract  Trails  Data Pump  Collector  Replicat
  6. 6. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Manager  Control process of Oracle Golden Gate  Must be running on each system in the Oracle Golden Gate configuration  One manger process can control many extract or replicat processes
  7. 7. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Extract  Extraction Mechanism in Oracle Golden Gate  Can be configured for the following  Initial loads  Change Synchronization  Can be captured from a data source of :  Table  Database Recovery logs or Transactional Logs  Third party capture module
  8. 8. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Trails  Supports the continuous extraction and replication of database changes  Golden Gate stores the records of captured changes temporarily on disk in a series of files called a trail  A trail can exist on  Source system (Extract Trail)  Intermediary system  Target System (Remote Trail)
  9. 9. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Data Pump  Secondary extract group within the source  Primary extract group “Extract” writes to a trail on the source  Data Pump reads the trail and sends the data over the network to a remote trail on the target  Can perform data filtering, mapping and conversion or it can be configured pass through mode.
  10. 10. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Collector  Runs on the target system  Receives extracted database changes that are sent by extract and write them to a Trail file  Can receive information from only one Extract process, So there is one collector for each extract that you use.  Collector terminates when the associated extract process terminates
  11. 11. Copyright © 2017 Tech Mahindra. All rights reserved. Overview of Replicat  Runs on the target system  Reads the trail on the target system  Re-constructs the DML or DDL operation and applies them to the target database  Like the extract can be configured for initial loads and change synchronization
  12. 12. Copyright © 2017 Tech Mahindra. All rights reserved. Golden Gate Supports  Business continuance & High Availability  Zero Downtime migration  Data Integration  Live Reporting, Real time Data Warehousing  Live Standby database  Supports Heterogeneous environments. Multiple business requirements:
  13. 13. Copyright © 2017 Tech Mahindra. All rights reserved. Supported Databases & Methods
  14. 14. Copyright © 2017 Tech Mahindra. All rights reserved. Logical Architecture of Golden Gate
  15. 15. Copyright © 2017 Tech Mahindra. All rights reserved. Supported Topologies
  16. 16. Copyright © 2017 Tech Mahindra. All rights reserved. Source / Prod Server Golden gate replication Require Live Production Data Target Server Requesting data Performance impact Load Balancing Live data from Target Real time access scenario
  17. 17. Copyright © 2017 Tech Mahindra. All rights reserved. INDIA USA China Business User BI Data Replicating Data Replicating Data Replicating User requesting data Data received Item Brand Qty Gend er Jeans Lee Cooper 300 Male Jacket Roadste r 150 Female Item Brand Qty Gend er Jeans Lee Cooper 200 Male Jacket Roadste r 200 Female Item Brand Qty Gend er Jeans Lee Cooper 120 Male Jacket Roadste r 400 Female Item Country Total Qty Jeans India 200 Jeans USA 300 Jeans China 120 Business Scenario
  18. 18. Copyright © 2017 Tech Mahindra. All rights reserved.

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