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Symfoware Analytics Server Technology

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.

Technology Overview 

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
High-speed processing
Column store, automatic column store indexing, full data compression in indexing
Performance
Response time
10 to 100 times faster than RDB
Concurrent execution
Even load distribution across cores
Tuning
Not required
Data compression
20% to 50%
Operation
Scalability
Ability to get started with single core (core license)
Upgrade
CPU and Storage can be upgraded independently
Redundancy
Cold standby

Symfoware Analytics Server offers greater performance

Column storage
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.

Oracle features
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.


Templates:
Category Template Description
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.

Data Processing Features:
Category Description
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
Trim padding
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