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Big Data in Medical Image Processing
Published in R. Suganya, S. Rajaram, A. Sheik Abdullah, Big Data in Medical Image Processing, 2018
R. Suganya, S. Rajaram, A. Sheik Abdullah
A column store database is a type of database that stores data using a column oriented model and is shown in the Figure 7. A column store database can also be referred to as a: Column database, Column family database, Column oriented database, Wide column store database, Wide column store, Columnar database and Columnar store. Column store databases are considered NoSQL databases, as they use a different data model to relational databases.
Web Databases
Published in Akshi Kumar, Web Technology, 2018
Modern application developers transact with massive volumes of new, rapidly changing data types, including structured, semi-structured, unstructured, and polymorphic data. Developing a clearly defined, well-organized schema is impossible for such massive amounts of unstructured data. NoSQL databases offer a schema-less alternative to their traditional counterparts, providing greater flexibility. Thus, instead of tables, NoSQL databases are document-oriented. This way, non-structured data (such as articles, photos, social media data, videos, or content within a blog post) can be stored in a single document. Based on the method of representation of data in databases, NoSQL databases can be categorized as follows: Key-value model: The least complex NoSQL option, which stores data in a schema-less way that consists of indexed keys and values. Examples include Cassandra, Azure, LevelDB, and Riak.Column store or wide-column store: Stores data tables as columns rather than rows. This is more than just an inverted table—sectioning out columns allows for excellent scalability and high performance. Examples include HBase, BigTable, and HyperTable.Document database: Follows the key-value concept and adds more complexity—each document in this type of database has its own data and its own unique key, which is used for retrieval. This is a great option for storing, retrieving, and managing data that is document-oriented but still somewhat structured. Examples include MongoDB and CouchDB.Graph database: Composed of two elements—a node and a relationship. Each node represents an entity (a person, place, thing, category, or other piece of data) and each relationship represents how two nodes are associated. New business requirements and big-data have made graph model a technology solution as it allows frequent schema changes, manages explosive volume of data, offers real-time query response time, and supports more intelligent data activation requirements. Examples include TigerGraph (formerly GraphSQL), Neo4j, and DataStax.
Enhanced adaptive partitioning in a distributed graph database
Published in Journal of Information and Telecommunication, 2021
Lucie Svitáková, Michal Valenta, Jaroslav Pokorný
The experiments were run on the JanusGraph, a graph database with a separate storage backend for which we selected Cassandra, a very popular wide column store. The choice of a particular product does, however, not influence our results as we monitor following system-independent measurements: intra-host communication improvement within a cluster counted as number of iterations of the algorithmcapacity of individual cluster nodes.