What is the main difference between a centralized repository and a distributed repository A. In a centralized repository, all commits from working copy go directly to the remote repository, whereas in a distributed repository system, everyone has a local copy of the repository on their local machine that acts as an intermediate step between the working copy and the remote repository B. A centralized repository has a single survey for the remote repository, where as a distributed repository uses the cloud for improved reliability. C. Centralized Repositories are used for cryptocurrency while distributed repositories are used for NFTS. OD. In a centralized repository, one person (the project lead) has the main repository in their working copy, and they handle all commits and updates, where as in a distributed there is no one project lead

What is the main difference between a centralized repository and a distributed repository A. In a centralized repository, all commits from working copy go directly to the remote repository, whereas in a distributed repository system, everyone has a local copy of the repository on their local machine that acts as an intermediate step between the working copy and the remote repository B. A centralized repository has a single survey for the remote repository, where as a distributed repository uses the cloud for improved reliability. C. Centralized Repositories are used for cryptocurrency while distributed repositories are used for NFTS. OD. In a centralized repository, one person (the project lead) has the main repository in their working copy, and they handle all commits and updates, where as in a distributed there is no one project lead

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Similar questions

When the MTTR drops to zero, what does it signify for availability? Is it possible to define this situation in terms of reality?
As MTTR drops to zero, what happens to availability? Does this seem like a situation that might be defined in terms of reality?
If you want to manage concurrency in distributed databases, you have to deal with the same problems as you do in any other distributed system. No, you don't need to use concurrency control solutions like 2PL (Two-phase locking) on a system that doesn't have any duplicate parts. Explain.
Suppose for a second that a technique known as snapshot isolation database is being used in order to provide security for the database of a financial institution.Do you have an example that explains how a nonserializable execution might be detrimental to the bank? If so, please share it with me. If so, please spread the word.
What happens to availability when the mean time between breakdowns (MTTR) gets closer and closer to zero? Is there a way to express this circumstance in a way that does it justice?
There are the same problems with managing concurrency that there are with other distributed systems. Distributed databases have the same problems. Is it necessary to use concurrency control solutions like 2PL (Two-phase locking) on a system that doesn't have any parts that are the same? Explain.
Consider a database with tables with parent tables and tables without parent tables. What differentiates controllers used to manage data for tables with and without parent tables?a) The routing algorithm to the controllerb) The number of methods in the controllerc) The controller method parameters, redirections, and model manipulationsd) Views are called from the models instead.
Consider a federated database system in which every local site ensures local serializability, and all global transactions are read only. a. Show by example that nonserializable executions may result in such a system. b. Show how you could use a ticket scheme to ensure global serializability.
A failed transaction must be aborted. True or False? If the precedence graph of a schedule is acyclic, the schedule is serializable. True or False?
Let's look at an airline database to see how snapshot isolation is used in practice. The airline, for instance, could agree to a nonserializable execution if it means better long-term outcomes.
To what extent does availability degrade as MTTR approaches zero? Can this be described with reasonable precision?
Consider a snapshot isolation-enabled airline database as an example. Describe a scenario where a nonserializable execution occurs but the airline is willing to put up with it in order to boost performance overall.