• # OLAP column-oriented database for real-time analysis and search of large scale
  • # Supports next-generation processing that can be simultaneously used for OLTP and OLAP tasks through parallel processing and transaction processing.
  • # Easy to utilize big data and can be applied to construction of large data mart (DM) and data warehouse (DW) as well as medium-to-small scale online transaction processing
  • # Designed to minimize security vulnerabilities to cope with various security enhancement needs such as data tampering prevention, column encryption and backup required by the Personal Information Protection Act
  • # Supports various features for data backup and transfer convenience
  • # Provides various features for convenient DBMS management
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  • Big data analysis / Business intelligence / Real-time log record and large scale analysis
  • Industry-standard interfaces (SQL, ODBC, JDBC, OLE DB)
  • Supports column encryption and log integrity (tampering prevention)
  • MPP-based parallel proceeding / Real-time data replication
  • GS certification level 1


  • Column-stored structures suitable for Data Warehouse / OLAP
  • Optimizes large data storage, extraction, analysis, and lookup tasks
  • Maximizes the utilization of system resource for MPP (Massive Parallel Processing)
  • Real-time data replication for fail-over
  • Transaction processing and simultaneous access user processing via MVCC
  • SQL-based RDBMS standard interface
    SQL 2003 standard / Schema-Table-View-Column-Index configuration
    PK, FK, View, Join, Trigger, Function, Stored Procedure configuration
    Programming interface - JDBC / ODBC / PHP / Perl / Python / C / C++
  • Supports various data types - CHAR, VARCHAR, TEXT, INT, BLOB, CLOB, URL (basic type), and user-defined data type
  • Partitioning - Horizontal, Range partition
  • Compression, encryption backup, and recovery with no temporarily-available space required
  • Runtime processing - Explain, Trace, Debug, Prepare
  • Data tampering prevention - Give Read-Only Table property to unauthorized users
  • Data protection – Record and control data access and input/output by basic account management and process authentication
  • Columnar encryption – Encrypt by column and save (validated encryption modules mounted)
  • Operation management - Text-based PetaSQL Client Tool and Orange for PetaSQL


  • Uses as operating setting DB or Repository DB for various solutions
    Verified quality and reliability after being used as a repository of operating and audit logs of WareValley DB access control system for years
  • Supports Orange for PetaSQL for user convenience


Various OS Support
Windows FreeBSD Platform Linux UNIX


Data Partitioning
Column Table
Range, Hash, List partition
Data Partitioning
No Name Age
01 Kang 30
02 Kim 31
03 Lee 32
04 Song 33
05 Park 34
Active-Slave - Real Data Replication
Column Table
Range, Hash, List partition
Parallel Processing
Multi-core CPU Processing
Big Size Memory
High-Gend storage Systems
User Mode Thread
Collaboration concurrent mode
Simultaneous multi-thread processing