Oracle Data Integrator Cloud Service (ODICS) – PART 1

Oracle is one of the prominent leaders in providing comprehensive data integration solutions that includes Oracle Data Integrator Cloud Service (ODICS), Oracle Data Integration Platform Cloud, Oracle Golden Gate, Oracle Enterprise Data Quality, Oracle Enterprise Metadata Management, and Oracle Stream Analytics.  ODICS provides continuous access to timely, reliable and heterogeneous data from both on-site and cloud solutions to support analytical and operational business needs.

ODICS Overview:

  • ODICS provides high-performance data transformation capabilities with its transparent E-LT architecture and extended support for cloud and big data applications.
  • ODICS supports all the features included in Oracle Data Integrator Enterprise Edition within its’ heterogeneous cloud service.
  • ODICS provides an easy-to-use interface to improve productivity, reduce development costs and decrease the total cost of ownership.
  • Oracle Data Integrator Cloud Platform is fully integrated with Oracle Process as a Service (PaaS) platform, such as Oracle Database Cloud Service, Oracle Database Exadata Cloud Service and/or Oracle Big Data Cloud Service to deliver data needs.
  • ODICS can work with third-party systems as well as Oracle solutions as shown in the below screenshot.
ODI On-Premises Integration with Cloud Services

ODI On-Premises Integration with Cloud Services


Cloud E-LT Architecture for High Performance vs Traditional ETL Approach:

  •  Traditional ETL software is based on proprietary engines that execute row by row data transformations, thus limiting performance.
  • We can execute data transformations on the target server by implementing an E-LT architecture based on your existing RDBMS engines and SQL.
  • The E-LT architecture gathers data from different sources, loads into the target and performs transformations using the database power.
  • While utilizing existing environment data infrastructures, Oracle Data Integrator delivers flexibility by using target server for data transformations thereby minimizing network traffic.
  • The new E-LT architecture ensures the highest performance possible.
ODICS ELT vs ETL Architecture Differences

ODICS ELT vs ETL Architecture Differences


Oracle Data Integrator Architecture Components:

The Oracle Data Integrator (ODI) architecture components include the below feature sets.


ODI SDK Java-based API for run time and scheduling Operations.
ODI Studio Designers’ studio to manage connections, interface designs, development, and automation including scheduling.
ODI Standalone Agent It can be configured in a standalone domain and managed by WebLogic Management Framework.


This is the Java EE agent based on the Java EE framework that runs on a WebLogic domain a Managed Server configured in a WebLogic domain. This feature set only comes with Enterprise Installation.
ODI Standalone Agent Template Domain files that are required when Oracle WebLogic Server is not handling your Oracle Data Integrator installation. This feature set is accessible only with the type of Standalone Install.
ODI Console As an alternative to certain features of ODI Studio, we can access the web-based console available to assigned users.
FMW Upgrade This is the upgrade assistant used to upgrade the Oracle Data Integrator version from 11g to 12c.
Repository Creation Utility The Repository Creation Utility (RCU) is used to create database schemas and included with the Standalone Installation type. Enterprise Installation does not include RCU but RCU is included with the installation of Oracle Fusion Middleware infrastructure distribution.


ODICS Architecture

ODICS Architecture


New / Enhanced Big Data and Cloud Features within ODICS:

 ODICS continues to evolve with technological advancements for Big Data and Cloud Knowledge Modules for better transformations.

Big Data Features:

  • Spark Knowledge Modules (KM) Improvement: The emphasis was on producing high-performance, and easy-to-read code (Spark) instead of handwritten scripts. Spark KMs now leverage the latest features such as Dataframes from Apache Spark 2.x to speed up the ODI processes.
  • Spark KMs support in Knowledge Module Editor: The Spark KMs are now fully supported and can be customized as per specific needs.
  • Hadoop Complex Types Enhancements: ODI enhances its support capability to Apache HDFS and Kafka Architecture.
  • Big Data Configuration Wizard: The Big Data Configuration Wizard is now updated with new templates for the current Cloudera distribution.
Spark KMs In Knowledge Module Editor

Spark KMs In Knowledge Module Editor


Cloud Features:

  • RESTful Service Support: ODICS can invoke RESTful Service in Topology configurations that include RESTful Service connectivity, resource URI, methods, and parameters.
  • Business Intelligence Cloud Service (BICS) Knowledge Modules: BICS is now supported out of the box in ODICS.
  •  Connectivity with Salesforce: ODICS is fully certified with and now includes a JDBC driver for this technology out of the box.
ODI Integration With Salesforce

ODI Integration With Salesforce


In the next part, we will focus on more key feature highlights within ODICS.


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