Distributed Database Management System (DDBMS) Platform

A Distributed Database Management System (DDBMS) Platform is a DBMS platform that is a distributed system and can manage distributed data.

• Context:
  • It can range from being a Distributed Non-Relational DBMS to being a Distributed Relational DBMS.
  • It can range from being a Distributed Column-based DBMS to being a Distributed Row-based DBMS.
  • It can range from being a Homogeneous DDBMS to being a Heterogeneous DDBMS.
  • It can range from being a Batch-Oriented DDBMS to being a Real-Time DDBMS.
  • It can range from being a Non-Partitioned, Non-Replicated DDBMS, to being a Partitioned, Non-Replicated DDBMS, to being a Non-Partitioned, Replicated DDBMS, to being a Partitioned, Replicated DDBMS.
  • It can (often) be a Highly-Scalable DBMS.
  • …
• Example(s):
  • a Bitcoin Ledger.
  • a Federated DBMS.
  • a NewSQL DBMS, such as: Google Spanner.
  • a Geo-Replicated System, such as Google Spanner.
  • …
• Counter-Example(s):
  • a Single-Server DBMS, such as a local database.
• See: Distributed Key-Store, Bitcoin, Network Servers.

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References

2016

• (Wikipedia, 2016) ⇒ http://wikipedia.org/wiki/Distributed_database Retrieved:2016-2-8.
  • A distributed database is a database in which storage devices are not all attached to a common processing unit such as the CPU, and which is controlled by a distributed database management system (together sometimes called a distributed database system). It may be stored in multiple computers, located in the same physical location; or may be dispersed over a network of interconnected computers. Unlike parallel systems, in which the processors are tightly coupled and constitute a single database system, a distributed database system consists of loosely coupled sites that share no physical components. System administrators can distribute collections of data (e.g. in a database) across multiple physical locations. A distributed database can reside on network servers on the Internet, on corporate intranets or extranets, or on other company networks. Because they store data across multiple computers, distributed databases can improve performance at end-user worksites by allowing transactions to be processed on many machines, instead of being limited to one. Two processes ensure that the distributed databases remain up-to-date and current: replication and duplication. # Replication involves using specialized software that looks for changes in the distributive database. Once the changes have been identified, the replication process makes all the databases look the same. The replication process can be complex and time-consuming depending on the size and number of the distributed databases. This process can also require a lot of time and computer resources.
    1. Duplication, on the other hand, has less complexity. It basically identifies one database as a master and then duplicates that database. The duplication process is normally done at a set time after hours. This is to ensure that each distributed location has the same data. In the duplication process, users may change only the master database. This ensures that local data will not be overwritten.
  • Both replication and duplication can keep the data current in all distributive locations.

    Besides distributed database replication and fragmentation, there are many other distributed database design technologies. For example, local autonomy, synchronous and asynchronous distributed database technologies. These technologies' implementations can and do depend on the needs of the business and the sensitivity/confidentiality of the data stored in the database, and hence the price the business is willing to spend on ensuring data security, consistency and integrity.

    When discussing access to distributed databases, Microsoft favors the term distributed query, which it defines in protocol-specific manner as "[a]ny SELECT, INSERT, UPDATE, or DELETE statement that references tables and rowsets from one or more external OLE DB data sources". Oracle provides a more language-centric view in which distributed queries and distributed transactions form part of distributed SQL. Today the distributed DBMS market is evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases. These databases are increasingly supporting distributed database architecture that provides high availability and fault tolerance through replication and scale out ability. Some examples are Aerospike, Cassandra, Clusterpoint, ClustrixDB, Couchbase, Druid (open-source data store), FoundationDB, NuoDB, Riak and OrientDB. The block chain technology popularised by bitcoin is an implementation of a distributed database.

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