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NEW DATABASE TECHNOLOGIES

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Albert Alexander Greiff Salgado
Mind Map by Albert Alexander Greiff Salgado, updated more than 1 year ago
Albert Alexander Greiff Salgado
Created by Albert Alexander Greiff Salgado over 6 years ago
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NEW DATABASE TECHNOLOGIES
  1. Core business functions and enterprise transaction processing:
    1. The related database is the one that administers the functions of payments, income I rake of the managings of the company with an interface that possesses the principal uses of the empreza, principal mind is the database that guards the information.
    2. Analytics and business intelligence:
      1. It is the option of environment of database that depends on the type that is realized, most of information that the analyst is accessible enters it is big information as haddop. this information is placed in 62 % in a database in the cloud and another per cent of 61 % it is located in NoSQL.
      2. IT operational data (logs, systems monitoring
        1. The professionals in the database rapidly can be in he her was structuring of the database and to open tests and to add information to the platform. In Microsoft Excel or database of access where one guards the information.
        2. Special projects
          1. The projects of the companies become by business managers, technical personnel and professionals, Microsoft was the one who was storing principally the database that it stores.Between the directors of information who answer to the study of dbta, 41 % of users hadoop mentions special projects as a case of key employment for the platform followed in 35 % of users of database of cloud.
          2. Security and compliance:
            1. In this area you need a database that is completely safe, the database manager that is responsible for this system are relational.
            2. Real-time or sub-second processing and response requirements:
              1. In this area it databases with low latency, where the data is sent to a random access memory of computers, in this case memory databases used are needed.
              2. Unstructured data analytics:
                1. In this case the relational databases are not as necessary as Hadoop file systems that make these files more manageable and accessible are used.
                2. Developer resources (configuration information):
                  1. In this case you need a fast database to call and deployment data, in this case, databases are used in the cloud or databases quick and simple data.
                  2. Web applications:
                    1. this case it is better not to use a SQL database (key-value) data, as they are simple and quick.
                    2. Ecommerce applications:
                      1. In this case you can have no previous SQL data base (key-value) Back-end databases, are a combination
                      2. Testing and pilot projects:
                        1. In this area you need to use databases with large capacity cloud.
                        2. Peripheral/branch office support:
                          1. access via the network to a central database. As a branch location is likely to be transaction-focused, a cloud database may be needed to support access.
                          2. Embedded devices and applications:
                            1. In this case databases that can be run remotely, requiring little maintenance, high security is needed. You can use relational databases.
                            2. Mobile applications:
                              1. At this level, a relational database in which to store local data allow to be stored and managed locally used.
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