Postgres Plus Connector for Hadoop
From the webpage:
The Postgres Plus Connector for Hadoop provides developers easy access to massive amounts of SQL data for integration with or analysis in Hadoop processing clusters. Now large amounts of data managed by PostgreSQL or Postgres Plus Advanced Server can be accessed by Hadoop for analysis and manipulation using Map-Reduce constructs.
EnterpriseDB recognized early on that Hadoop, a framework allowing distributed processing of large data sets across computer clusters using a simple programming model, was a valuable and complimentary data processing model to traditional SQL systems. Map-Reduce processing serves important needs for basic processing of extremely large amounts of data and SQL based systems will continue to fulfill their mission critical needs for complex processing of data well into the future. What was missing was an easy way for developers to access and move data between the two environments.
EnterpriseDB has created the Postgres Plus Connector for Hadoop by extending the Pig platform (an engine for executing data flows in parallel on Hadoop) and using an EnterpriseDB JDBC driver to allow users the ability to load the results of a SQL query into Hadoop where developers can operate on that data using familiar Map-Reduce programming. In addition, data from Hadoop can also be moved back into PostgreSQL or Postgres Plus Advanced Server tables.
A private beta is in progress, see the webpage for details and to register.
Plus, there is a webinar, Tuesday, November 29, 2011 11:00 am Eastern Standard Time (New York, GMT-05:00), Extending SQL Analysis with the Postgres Plus Connector for Hadoop. Registration at the webpage as well.
A step towards seamless data environments. Much like word processing now without the “.” commands. Same commands for the most part but unseen. Data is going in that direction. You will specify desired results and environments will take care of access, processor(s), operations and the like. Tables will appear as tables because you have chosen to view them as tables, etc.