This chapter describes the benefits of a distributed database, the benefits of distributed database systems, and Oracle`s distributed database architecture. This chapter contains: Clusterpoint eliminates the complexity, scalability issues, and performance limitations of relational database architectures. Data is managed in XLM or JSON format via open APIs. Because Clusterpoint is a schemaless document database, it eliminates the scalability and performance issues that most relational database architectures face. Vertically fragmented data requires the use of copies of the primary keys that are available in each section of the database and accessible by each branch. Vertically fragmented data is used when a company`s branch and central location interact with the same accounts in different ways. A distributed database is a collection of several interconnected databases that are physically distributed to different locations that communicate over a computer network. In addition to distributed database replication and fragmentation, there are many other distributed database design technologies. For example, local autonomy, synchronous and asynchronous distributed database technologies. The implementation of these technologies may and will depend on the needs of the Company and the sensitivity/confidentiality of the data stored in the database and the price the Company is willing to pay to ensure the security, consistency and integrity of the data.
Distributed NoSQL databases apply the principles of database systems more comprehensively because NoSQL databases store data in a distributed manner. Data mapping in distributed database environments can be managed to optimize the cost or speed of access internationally. Two processes ensure that distributed databases remain up-to-date: replication[3] and replication. The main benefits that distributed databases bring to the game are improved performance, massive scalability, and always-on reliability. Processing overhead – Even simple operations can require a lot of additional communication and computation to ensure data consistency across locations. 1. Replication – In this approach, the entire relationship is stored redundantly in 2 or more locations. If the entire database is available in all locations, it is a fully redundant database. Therefore, systems retain copies of the data during replication. Reorganized data is data that has been adapted or modified for decision support databases.
Reorganized data is typically used when two different systems process transactions and decision support. Decision support systems can be difficult to maintain, and processing online transactions requires reconfiguration when many requests are made. It must therefore be managed in such a way as to appear to consumers as a single database. However, in heterogeneous distributed systems, SQL statements issued from an Oracle database to a remote database server outside of Oracle are limited by the capabilities of the remote database server and associated gateway. For example, if a remote or distributed query contains advanced Oracle SQL functionality (for example, an outer join), the function might need to be executed by the local Oracle database. Advanced SQL features of remote updates (such as an outer join in a subquery) are not supported by all gateways. For more information about your system`s features, see the SQL*Connect documentation. A distributed key-value database can be configured to store the same data on multiple nodes across multiple sites. If only one node fails, the data is still available. You do not need to wait for the database to be restored. A geographically dispersed database manages simultaneous nodes across geographic regions to ensure resiliency in the event of a regional power or communication outage.
The ability to store a single database on multiple computers requires a data replication algorithm that is transparent to users. While there are many distributed databases to choose from, Apache Ignite, Apache Cassandra, Apache HBase, Couchbase Server, Amazon SimpleDB, Clusterpoint, and FoundationDB are examples. Homogeneous databases are then divided into stand-alone and non-stand-alone types. Independent means that each database is autonomous and works on its own. A management program integrates them and uses message transmission to communicate data changes. A common misconception is that a distributed database is a weakly connected file system. In reality, it is much more complicated than that. Distributed databases involve transaction processing, but are not synonymous with transaction processing systems.
Administrators can reduce the communication costs of distributed database systems when data is close to where it is most frequently used. This is not possible in centralized systems. The following diagram shows an example of a homogeneous database: Distributed database management systems simply extend the hierarchical naming model by applying unique database names within a network. This ensures that an object`s global object name is unique in the distributed database and that references to the object`s global object name can be resolved between system nodes. To enable complex SQL queries, most NoSQL databases use a multi-model architecture. Under the hood, multi-model is equivalent to running two separate databases. However, HarperDB immediately supports SQL and NoSQL use cases with a powerful data store for a single model. With flexible, custom APIs enabled by custom functions and a simple HTTP/s interface, you can build your entire application in one place, and HarperDB scales your application from proof of concept to production. When errors occur in centralized databases, the system shuts down completely. However, if a component fails in distributed database systems, the system continues to operate at reduced performance until the error is resolved. Better responsiveness – When data is distributed efficiently, user requests from local data can be met themselves, allowing for a faster response. On the other hand, in centralized systems, all processing requests must go through the mainframe, which increases the response time.
Modular development – If the system is to be extended to new sites or units in centralized database systems, the action requires significant effort and disruption of existing operation. However, in distributed databases, the job requires only the addition of new computers and local data to the new site, and possibly the connection to the distributed system without interrupting current functionality. Database links are essentially transparent to users of a distributed database because the name of a database link is the same as the global name of the database referenced by the link. For example, the following statement creates a database link in the local database. The database link named SALES.DIVISION3.ACME.COM describes a path to a remote database with the same name. Distributed databases solve a variety of problems, such as availability, fault tolerance, throughput, latency, scalability, and many other issues that can arise from using a single computer and database. A centralized distributed database management system (DBMS) manages distributed data as if it were stored in a physical location. The DBMS synchronizes all data operations between databases and ensures that updates to a database automatically mirror databases in other locations.
At this point, any application or user connected to the local database can access data in the SALES database by using global object names when referencing objects in the SALES database. The SALES database link is implicitly used to facilitate connection to the SALES database. For example, consider the following remote query that references the SCOTT remote table. EMP in the SALES database: Need to share data – Different organizational units often need to communicate with each other and share their data and resources.