Data warehouse software employs a high-speed query engine with the data processing tools to ensure instant accessibility of information. Familiar tools can be deployed for ad hoc data analysis.
PostgreSQL open standard interface
The PostgreSQL interface can be linked with a variety of ADV/OLAP tools. Providing multi-faceted analysis with high-granularity to identify new trends and developments.
|Symfoware Analytics Server|
||Column store, automatic column store indexing, full data compression in indexing
||10 to 100 times faster than RDB
||Even load distribution across cores
||20% to 50%
||Ability to get started with single core (core license)
||CPU and Storage can be upgraded independently
Symfoware Analytics Server offers greater performance
Access is directly targeted to the columns required for data retrieval, this system reduces disk I/O and avoids conflicts between resources, providing a solution to the problem of processing large data volumes within effective timeframes.
High compression in bit units
Duplicate row data is removed prior to storage to minimize both memory usage and data volumes for faster processing speeds.
Supports Oracle compatible syntax and NCHAR
Templates and Data Preparation
Standard templates for manipulating tables and associated data. Data Processing templates can be created simply by modifying the template parameters.
A drag-and-drop interface is provided for simple and intuitive customization. It is easy to prepare data by modifying the combination of template components. This way data can be prepared on site for analysis in a minimal amount of time.
|Data operations||Columnartable storage||Stores the data written in a CSV file to a columnar table created beforehand.|
|Table storage||Stores data written in a CSV file to a table created beforehand.|
|Columnartable row refinement||Filters data stored in a columnar table by row and stores the data in a columnar table that has the same columns as the extraction target.|
|Table operations||Columnartable creation||Creates a columnar table in a database.
Data is read by column; suitable for large data volumes that are rarely updated.
|Columnartable deletion||Deletes a columnar table from a database.|
|Table creation||Creates a table in a database.
Data is ready by record; best for small data volumes that are constantly updated.
|Table deletion||Deletes a table from a database.|
|Table permission||Grants a privilege for the specified table to the specified user.|
|Table permission cancellation||Revokes the privilege for the specified table for the specified user.|
|Tablelist acquisition||Obtains a list of tables from a database and writes it to a text file.|
|Table definition acquisition||Obtains a table definition from a database and writes it to a text file.|
|Format conversion||Binary CSV interconversion
Binary XML interconversion, CSV-XML interconversion
|Character code conversion
||EBCDIC, SJIS, EUC, IBM, JEF, Unicode character code conversion|
|Item editing||Change item order, select items, add items|
|Use code conversion table to map master code data|
|Data type conversion|
|Combine items, split items|
|Edit text strings (alternative characters, hiragana/katakana, single-byte/double-byte, upper case/lower case)|
|Four arithmetic operators, value table conversion|
|Convert to date format|
|Define item conditions|
|Set record sequence number|
|Calculate/set date/time difference|
|Record editing||Extract conditions (sorting)|
|Sort, join/union, aggregate|
|Join multiple key items|
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