Development status Active Operating system | Written in Java License Apache License 2.0 | |
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Developer(s) Apache Software Foundation Stable release 1.7.2 / June 21, 2016 (2016-06-21) | ||
Apache Accumulo is a computer software project that developed a sorted, distributed key/value store based on the BigTable technology from Google. It is a system built on top of Apache Hadoop, Apache ZooKeeper, and Apache Thrift. Written in Java, Accumulo has cell-level access labels and server-side programming mechanisms. Accumulo is the third most popular NoSQL wide column store according to the DB-Engines ranking, behind Apache Cassandra and Hbase as of 2015.
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History
Accumulo was created in 2008 by the US National Security Agency and contributed to the Apache Foundation as an incubator project in September 2011.
On March 21, 2012, Accumulo graduated from incubation at Apache, making it a top-level project.
Controversy
In June 2012 the US Senate Armed Services Committee (SASC) released the Draft 2012 Department of Defense (DoD) Authorization Bill, which included references to Apache Accumulo. In the draft bill SASC required DoD to evaluate whether Apache Accumulo could achieve commercial viability before implementing it throughout DoD. Specific criteria were not included in the draft language, but the establishment of commercial entities supporting Apache Accumulo could be considered a success factor.
Cell-level security
Apache Accumulo extends the BigTable data model, adding a new element to the key called Column Visibility. This element stores a logical combination of security labels that must be satisfied at query time in order for the key and value to be returned as part of a user request. This allows data of varying security requirements to be stored in the same table, and allows users to see only those keys and values for which they are authorized.
Server-side programming
In addition to Cell-Level Security, Apache Accumulo provides a server-side programming mechanism called Iterators that allows users to perform additional processing at the Tablet Server. The range of operations that can be applied is equivalent to those that can be implemented within a MapReduce Combiner function, which produces an aggregate value for several key-value pairs.