Annotated Bibliography On Database Algorithms

Asymmetric clustering: one host runs the database application while the other host simply monitors it. If the server fails, the monitoring host becomes the active server. This is appropriate for providing redundancy. However, it does not utilize the potential processing power of both hosts.

Asymmetric clustering: in this, one host will run the database and other host continues checking it. In the event that host getting to the database application comes up short then different begins working. This suits for giving excess. In any case, it can't utilize the potential work of both

In a distributed database system, all the databases or the storage devices are not connected to a single common processing unit like CPU. The various data may be stored at different physical locations in multiple computers that are located in the same physical location; or they may be inter-connected over a network. In other words, distributed database system consists of various data locations but they do not share any physical components.

The Proliferation and advances in computer network have led to increase Distributed database system In Distributed Database Different user are connected for accessing the data. In distributed database the data from the single local computer can be transferred or distributed on various computer connected at the same physical location. The Data from the database can be distributed to the multiple physical loacation. It is a powerful technology with great potential to help companies focus on how to transfer information by their main branch to the different sub-branch or collected data from their sub branch to their main branch. This is not the easy as we se there is different types of corrupted data on the remote computers. There is also possibility of problem in physical location. The network must be failed in between data transfer. There is also possibility of hacking data in between tansfering. There is some techniques used by Distributed Database for handling this types of problems during information transfering over the different networks.

As a Business System Analyst, most of my responsibilities involve working with big data. Data management is key to the success of any company. This includes, data security, data availability and assessment. Many companies need to replicate data that is both in cloud or other infrastructures for various purposes including; uptime and resilience, remote backup and storage, branches and other offices and building business in a box to mention a few (KLEYMAN, 2013). If data replication in cloud environment is very important, it is therefore important that companies ensure that they used the best technique in carrying out this activity. This documents provides the analysis of different techniques of data replication in cloud environment. Also, included in this document are my findings on the analysis, recommendation and conclusion

Distributed database technologies are an emerging market and bound to have a significant impact on data processing in the upcoming years. Research states that the introduction of commercial products there is more expectation that distributes database management system will take over a centralized database within the near future. Even though DDBMS is changing technologies, there are still issues. This paper is about the lack of security in a distributed database and how we can improve it in many ways. The distributed database is a collection of database, stored at various sites of the network; therefore, security is an important issue.

In recent years, the distributed database system has been emerging as an important area of information processing, and its popularity is increasing rapidly. A distributed database is a database that is under the control of a central DBMS in which not all storage devices are attached to a common CPU. It may be stored on multiple computers located in the same physical location, or may be dispersed over a network of interconnected computers. Collections of data (e.g., in a database) can be distributed across multiple physical locations. In short, a distributed database is a logically interrelated collection of shared data, and a description of this data is physically distributed over a computer network. A

Microsoft SQL Server is a product of Microsoft and a relational database system sustain semi-structured and structured data. It helps user to create durable, atomic and consistent transactions. . It provides support for data clustering and database mirroring. An SQL cluster server helps disburse workload among various servers and provide data partitioning. On the other hand database mirroring provides creation of mirrors depend on certain predefined database triggers included transaction logs.

For any organization the collection and storage of data have always been a primary concern. Large organizations nowadays use a database system to address this task. However, the earliest solution is a file-based system, and it is still in use in many small firms today.

DBMS is the main software tool of database management approach because it controls the creation, maintenance, and use of the databases of an organization and its end users (O’Brien, 2009). In the past, Dell IT group ran its SCM database applications on large, expensive, proprietary servers based on the UNIX® OS. As company grew, a larger and more powerful server was required thus DellPowerEdge servers was used to enabled Dell IT to create cost-effective, highly scalable systems using Oracle Real Application Clusters (RAC) 10g. By sharing a

There is also a much talked about database called Cassandra which also needs to be discussed. It was originally developed by Facebook as open-sourced in 2008 [6]. Facebook was among the first to try the system for its inbox search system, which controls and stores in its disk space, and with the high performance of the system within its service level agreement requirements more applications like Netflix, Twitter etc. embraced Cassandra as their storage engine as well as backend for their streaming services [9]. What is Cassandra? Based on many definitions, Cassandra is a type of open source distributed database that is highly scalable, high performance designed to handle big amounts of data between many commodity servers that guarantees high availability without failure. Its main duty is high performance, also with its robust clusters among several data centers, as well as providing low latency operation for its various clients which is why businesses love it. It was written in Java language. Cassandra in accordance with research conducted on NoSQL systems concluded that its scalability, ability supersedes rest of the database management system with its largest number of nodes. Designed as a distributing system, which supports replication and multi replication as well as the ability to replace failed nodes without downtime [2]. Cassandra supports other open source like Hadoop, Apache Pig etc. It is similar with relational database since

Performance measurement is the process of collecting, analyzing and/or reporting of key defined metrics regarding the performance of database management components and the overall database management system.

Replication: It is process of maintaining two congruent databases such that even one crashes the other node can be used as a backup. As these databases are stored in different geographic locations there will be a significant reduction of network load.

Backup and recovery management. Through this function, it can help to prevent the outside threat to the database. Database management system can restore the

Data I record only one place in the database and it is not duplicated. • Users can share same data Similarly, the data of same database can be shared between different application program. • Most of the DBMS provide SQL as standard database access language. It is used to access data from multiple tables of a database. • The DBMS provides tools that can be used to develop application programs.