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Time series analysis (financial data, web logs, etc.) works best with row oriented databases. A traditional database consists of tables with data ordered by row (row-oriented). When data are organized by rows, data look-up can be done quickly by using a key-value to identify the row and then its associated data. When data are organized by column (column-oriented), operations on columns are extremely fast because there is no key-value look-up. This approach is used for time-series analysis. If you are a kdb+ user or are intrigued with time-series analysis, there are resources waiting for you. First, there is a free version of kdb+ (32 bit) available for download. The free version has all the functionality of the 64-bit version and can be used for commercial, non-commercial, or educational purposes.
A traditional database consists of tables with data ordered by row (row-oriented). When data are organized by rows, data look-up can be done quickly by using a key-value to identify the row and then its associated data. When data are organized by column (column-oriented), operations on columns are extremely fast because there is no key-value look-up. This approach is used for time-series analysis. If you are a kdb+ user or are intrigued with time-series analysis, there are resources waiting for you. First, there is a free version of kdb+ (32 bit) available for download. The free version has all the functionality of the 64-bit version and can be used for commercial, non-commercial, or educational purposes.
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