Abstract
The RDF data model is gaining importance for applications in computational biology, knowledge sharing, and social communities. Recent work on RDF engines has focused on scalable performance for querying, and has largely disregarded updates. In addition to incremental bulk loading, applications also require online updates with flexible control over multi-user isolation levels and data consistency. The challenge lies in meeting these requirements while retaining the capability for fast querying. This paper presents a comprehensive solution that is based on an extended deferred-indexing method with integrated versioning. The version store enables time-travel queries that are efficiently processed without adversely affecting queries on the current data. For flexible consistency, transactional concurrency control is provided with options for either snapshot isolation or full serializability. All methods are integrated in an extension of the RDF-3X system, and their very good performance for both queries and updates is demonstrated by measurements of multi-user workloads with real-life data as well as stress-test synthetic loads.
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