volume of data that needs to be scanned. When the query is too complex, the optimizer is no longer able to determine an optimal method and resorts to whole table scans to find the desired records, ignoring the indexing. A whole table scan on a moderate-sized table may take only seconds, but on the very large tables found in data warehouses, it can take several minutes. And when performing a complex query that involves many tables and many indices on those tables, whole table scans can force a single query to take hours or even days. Clearly, this is not acceptable for a system that is supposed to support rapid query and response, ad hoc query, reporting and unplanned exploration and discovery. The row oriented database creates need of reorganization
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What is different is the way that the database administrator has to think about data. While in a row-oriented database he thinks in terms of individual transactions, in a column-oriented database he has to think in terms of similar items derived from sets of transactions. From the indexing point of view, he has to pay more attention to the cardinality of the data, because an index is related with a subject, such as the balance account, and not with an entire transaction with all its fields. Decision-makers need a better access to information, in order to make accurate, fast and multi viewed decisions in a permanent changing environment. In both the types of databases the queries are almost same without any major change. Only some logical concepts have to be considered. Like when working with row-oriented database user have to think about the day to day transaction considering all attribute of each record but with column oriented database user have to consider the records of same attributes for some analytical processing.
Physical structure: The first table represents the physical storage of the record-based structure in RDBMS, which is the simplest. Variations like clustered indexing may change the sequence of the rows, but all rows, columns, and values will be stored as in the
What is different is the way that the database administrator has to think about data. While in a row-oriented database he thinks in terms of individual transactions, in a column-oriented database he has to think in terms of similar items derived from sets of transactions. From the indexing point of view, he has to pay more attention to the cardinality of the data, because an index is related with a subject, such as the balance account, and not with an entire transaction with all its fields. Decision-makers need a better access to information, in order to make accurate, fast and multi viewed decisions in a permanent changing environment. In both the types of databases the queries are almost same without any major change. Only some logical concepts have to be considered. Like when working with row-oriented database user have to think about the day to day transaction considering all attribute of each record but with column oriented database user have to consider the records of same attributes for some analytical processing.
Physical structure: The first table represents the physical storage of the record-based structure in RDBMS, which is the simplest. Variations like clustered indexing may change the sequence of the rows, but all rows, columns, and values will be stored as in the