Distributed Databases What is a Distributed Database A

Distributed Databases

What is a Distributed Database? A database which is distributed over some form of network to bring down the cost or the difficulty in accessing data and to increase the efficiency of the whole system. The software that runs it is called a Distributed Database Management System (DDBMS). http: //www. mahipalreddy. com /dbdesign/dbarticle 1. htm

Centralized Database All queries are served by a single datacenter (in MSU). Black lines indicate query paths.

Distributed Database Queries are served by the nearest datacenter (black lines). The datacenters each have communications channels to facilitate the transfer of data (red lines).

Advantages of Distributed Databases 1. More accessible by users (closer datacenter means faster connection) 2. Redundancy (more uptime because other datacenters can handle load if a datacenter fails) 3. Ability to grow (can add new datacenters without interrupting service) 4. Ability to change (datacenters can change technologies without impacting service) 5. Parallelism (more queries can be handled than having all funneled to single datacenter)

Homogenous Distributed Database A homogenous network of databases have identical software (and sometimes hardware) used at all sites (datacenters / servers). Software refers to the OS, DBMS, and schema of the data. This is nice because all the sites are well-understood by all, and optimizations useful for one site can be exported to others. It is easier to treat such a network as a single central database system.

Heterogeneous Distributed Database A heterogeneous network of databases use different software (i. e. OS, DBMS, schema) at different sites. Because of this, cooperation (human and computer-wise) between sites can be more difficult. But diversity can allow for optimization, and independence from any particular technology.

Components User Processor: Data Processor: User interface handler – interprets user commands when they are given in, and formatting the result sets when the request is answered Local query optimizer – it optimizes data access by choosing the best access path. For example, Local query optimizer decides which index to be used for optimally executing the given query. Semantic data controller – checks the integrity constraints and authorizations defined on database elements Global query optimizer and decomposer – devises a best execution strategy to execute the given user requests in minimal cost (in terms of time, processor, memory). Global execution monitor – this is the transaction manager. The transaction managers of various sites participating in a query execution communicate with each other as part of execution monitoring Local recovery manager – deals with the consistency of the local database. In case of failure, local recovery manager is responsible for maintaining a consistent database. Run-time support processor – it accesses the database physically according to the strategy suggested by the local query optimizer.

Components http: //www. springer. com/us/book/9781441988331

Global Execution Monitor Global execution monitor is the primary component of distributed databases which communicates with remote databases to coordinate the processing of a query. http: //photobucket. com/images/hall%20 monitor%20 badge