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New submitter rescrv writes "Key-value stores (like Cassandra, Redis and DynamoDB) have been replacing traditional databases in many demanding web applications (e.g. Twitter, Google, Facebook, LinkedIn, and others). But for the most part, the differences between existing NoSQL systems come down to the choice of well-studied implementation techniques; in particular, they all provide a similar API that achieves high performance and scalability by limiting applications to simple operations like GET and PUT.

HyperDex, a new key-value store developed at Cornell, stands out in the NoSQL spectrum with its unique design. HyperDex employs a unique multi-dimensional hash function to enable efficient search operations — that is, objects may be retrieved without using the key (PDF) under which they are stored. Other systems employ indexing techniques to enable search, or enumerate all objects in the system. In contrast, HyperDex's design enables applications to retrieve search results directly from servers in the system. The results are impressive. Preliminary benchmark results on the project website show that HyperDex provides significant performance improvements over Cassandra and MongoDB. With its unique design, and impressive performance, it seems fittng to ask: Is HyperDex the start of NoSQL 2.0?"


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This document provides statistics about the structure and content of the LOD cloud. It also analyzes the extend to which LOD data sources implement nine best practices that are either recommended W3C or have emerged within the LOD community.

All statistics within this document are based on the LOD data set catalog that is maintained on CKAN. This document contains a preliminary release of the statistics. If you spot any errors in the data describing the LOD data sets, it would be great if you would correct them directly on CKAN. For information on how to describe datasets on CKAN please refer to the Guidelines for Collecting Metadata on Linked Datasets in CKAN.

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