New-age Transactional Systems - Not Your Grandpa's OLTP
John Hugg discusses high volume transaction processing applications with high and low frequency profiles, and how VoltDB can be used for that purpose.
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Posted by Ryan Slobojan on May 14, 2008
The Compass project, an open source project based on Lucene which aims to simplify the integration of search into Java applications, recently released version 2.0. InfoQ spoke with Compass founder Shay Banon to learn more about this release and about what Compass provides to the Java community.
Banon identified the major features of this release as:
Compass also has a new project website at http://www.compass-project.org, and a complete listing of changes available.
Banon also described the Compass core features, and how Compass compares with Solr, Nutch and base Lucene:
Compass, at its core, aims to simplify the integration of search into any Java application. Compass tries to simplify the API when working with a search engine. The API should be very familiar for people who are used to ORM libraries. Another main feature of Compass is the ability to easily map a Java object model into the search engine as well as other formats such as XML and Map like structures. On top of that, Compass steps even further and provides seamless integration with ORM libraries, data grids, and other.
Regarding Lucene, Compass is built on top of Lucene. All of Lucene features are exposed and can be used with Compass, but Compass tries to simplify its usage, especially within your typical Java application. Regarding Solr, I guess it also aims at simplifying Lucene, but in a different way. It exposes an http service for indexing and searching, but I heard that an "embedded" version of it will be available as well. I guess the main difference stems from a different viewpoint on how search is integrated into an application. I will just note that creating an http search service on top of Compass is very simple and many users have done just that.
When asked about future plans for Compass, Banon stated that most of the features are driven by user demand. Potential future ideas include looking at different indexing formats such as JSON, more comprehensive and full-featured data grid integration to enable colocated indexing and searching, and a UI layer search integration to create a better out-of-the-box experience. Banon also added that all Compass feedback and help is greatly appreciated.
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John Hugg discusses high volume transaction processing applications with high and low frequency profiles, and how VoltDB can be used for that purpose.
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