Distributed Data Structure

What is a Distributed Data Structure?
A distributed data structure (DDS) is a self-managing storage layer designed to run on a cluster of workstations and to handle Internet service workloads.[1] After information has been mined across varius sites, it can be divided categorically. It contains a slew of service properties, high concurrency, high throughput, incrementally scalability, availability, and strict consistency of its data. DDS is a conventional data structure, such as a hash table, a tree, or a log.

Distributed Data Structure
DDS has a strictly defined consistency model: elements are atomic, in that any operation it completes entirely, or not at all. DDS have only a one copy equivalence, so even though data elements in a DDS are replicated, clients only can see a single, logical data item. There is a two-phase commits used to keep replicas coherent, and thus all clients see the same image of a DDS through its interface.

DDS's interface is more structured and at a higher level than that of a file system. Granularity of an operation is a complete data structure element rather than a set byte range. The set of operations over the data in a DDS is fixed by a small set of methods exposed by the DDS API, unlike an RDBMS in which operations are defined by the set of expressible declarations in SQL.

Common Uses
Often distributed databases are used by organizations that have numerous offices or storefronts in different geographical locations. It allows multiple storefronts to send data to the main node, and then at off-peak hours the whole database receives all the sent data and compiles it. Usually, a storefront which might not need for inconsistent central information from other branches, so it is easier to have a central office receive all the data, and the storefronts call pull any and all data that they might require.

Distributed databases may be beneficial in preserving the privacy of internet users. The more data that is being dealt with across websites, security becomes increasingly vulnerable. Through the use of horizontally distributed databases, no third party would be required to communicate across sites and the sites could communicate directly with each other (Joyce, 2015).