Distributed Database Management System helps in managing the distributed database. Distributed Database Management System is required  to maintains distributed database and make it transparent to clients. 

Distribute databases are becoming more common in data warehouse where high volumes of data need to be processed and many data consumers may be simultaneously accessing the data warehouse. Data flow freely over any network combination with the help of network protocols.

But since the very nature of distributed database is very fragmented as different data may be stored in different departmental locations, there needs to be a way to give the end user or data consumer the impression that he is accessing data from one logical system.

The constant flow or data from one computer server to a client and vice versa can also pose security threats as software data sniffers are easily available for stealing confidential information.

A Distributed Database Management System is used both in managing the data in the network in terms of handling data integrity and maintaining confidentiality and privacy. The Distributed Database Management System sits in a central application while managing a distributed database as if it were all stored on the same computer. The DDBMS constantly does it job of synchronizing data, ensuring that updates and deletions are done in correct fashion.

It also manages disparity of databases as well as their resulting disparate data. Since in a distributed database system, there are various computer servers handling different database, it may be that these computers are running on several disparate platforms. So when the disparate data converges at the central data warehouse, the DDBMS will be responsible for transforming the data into one unified data format that can fed to an enterprise business intelligence system.

The Distributed Database Management System basically addresses the following technical processes:

Replica synchronization – This is about synchronizing data based on relatively smaller transactions where the said transactions may consist of several read and write operations on the server. But some applications can take relatively bigger data production jobs can write a whole file which can be a relatively large transactional file.

Synchronous and asynchronous replication – Replication may be done through synchronous or asynchronous or batch replication method which makes replicas be in synch (synchronous) or out of sync (asynchronous) for a certain period of time. Update reconciliation may be done at certain intervals such as every hour or every night.

Network servers and loads – This refers to the management of computer on the network networks nodes which can act either as server or client or both server and client at certain circumstances. Under this area, other important considerations include traffic management and security aspects.

Heterogeneous data stores management – Different computer servers may be implemented on different platforms so support for heterogeneous data store should be greatly considered. Different kinds of data may be stored in different formats by different vendors. Even in the case of two different database paradigms namely relational and object oriented, a DDBMS needs to consider this aspect. The standard protocol used for directory information such as Lightweight Directory Access Protocol (LDAP) falls under this consideration.

The different types of data implementations like relational, flat files, deductive, dimensional, hierarchical, object oriented, object relational, temporal and XML data stores are all under the DDBMS in a distribute database environment.

While many distributed database management system software applications are available from a wide variety of software applications vendors, it to carefully plan before buying one which suits the needs of the business organization. Different organizations of varying sizes and financial capabilities have differing needs so the appropriate solutions should be acquired.