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Phil Chung, Oracle

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Phil Chung is an Oracle Principal Solution Architect in the area of real time in-memory data processing, in memory data grids, and grid architectures.  In his previous roles, he has worked as part of a SWAT team of solution architects dedicated to Coherence and also as a pre-sales consultant focused on TimesTen.  With a software development background spanning over 10 years in capital markets, wireless media, and online gaming, he has worked on trading systems for broker/dealers, messaging servers and telecommunications gateways.  Phil works with customers to help architect, educate and evangelize best practices for in memory solutions to meet their business needs.  Phil is based in the Oracle New York office at 520 Madison Avenue.

Presentation: ""EclipseLink" Data Services for the Cloud"

Time: Wednesday 16:50 - 17:50

Location: Roebling/Gleason


Cloud platforms provide new opportunities but they bring new challenges for applications developers.  EclipseLink, known principally as the JPA 2.0 reference implementation, is responding to these challenges by evolving to provide new Java data services that address the unique needs of cloud applications. In this session we’ll dive into these new services and see how to leverage EclipseLink in both in the back end for data persistence and on the front end to build RESTful services that support HTML5 clients.

  • NoSQL/Polyglot Persistence—supporting storage and querying of JPA entities in NoSQL databases and the ability to combine relational and non-relational data in a single application.
  • Multitenancy—isolating each tenant’s data by data source, schema, table, or at the row level (including support for Oracle Database Virtual Private Database).
  • EclipseLink JPA-RS—exposing JPA mapped entities over REST either as XML with JAXB or JSON with EclipseLink JSON-B. 
  • EclipseLink JSON-B—providing Java/JSON binding similar to JAXB’s Java/XML binding. With JSON-B, developers can easily marshall their Java domain model to and from JSON which is the preferred format for HTML5/JavaScript clients.
  • Data Partitioning—accessing extremely large data sets through a variety of data sharding/partitioning strategies for managing data across databases and schemas
  • Grid Caching—integrating with data grid products and frameworks to scale out caches into large clusters