• OLAP-based, column-oriented database for analyzing and searching large volumes of data in real time
  • Enables next-generation processing for simultaneous OLTP and OLAP operations through parallel and transactional processing
  • Designed to minimize security vulnerabilities in compliance with various requirements of the Personal Information Protection Act, ensuring security enhancements such as data forgery prevention, column encryption, and backups
  • Supports a variety of features for easier data backup and transfer
  • Provides a wide range of features for easier DBMS management


PetaSQL allows the convenient utilization of big data and can be applied not only to building a large-scale data mart (DM)
but also to small and medium-scale online transaction processing

Big Data Analysis / Business Intelligence / Real-Time Logging & Large-Scale Analysis Icon

Big Data Analysis / Business Intelligence / Real-Time Logging & Large-Scale Analysis

Industry-standard Interfaces (SQL, ODBC, JDBC, OLE DB) Icon

Industry-standard interfaces (SQL, ODBC, JDBC, OLE DB)

Support for Column Encryption / Log Integrity (Anti-Tampering) Icon

Support for Column Encryption / Log Integrity (Anti-Tampering)

MPP-Based Parallel Processing / Real-Time Data Replication Icon

MPP-Based Parallel Processing / Real-Time Data

GS Tier 1 Certification Icon

GS Tier 1 Certification


  • Column Stored structure that is suitable for data warehouse/OLAP
  • Optimizes the tasks that store, extract, analyze, and view large data
  • Maximizes the utilization of system resources for Massive Parallel Processing (MPP)
  • Real-time data replication for a failover
  • Concurrent access users processed through transaction processing and MVCC
  • Standard RDBMS interface based on SQL
    • - Composed of SQL 2003 Standard / Schema-Table-View-Column-Index
    • - Composed of PK, FK, View, Join, Trigger, Function, and Stored Procedure
    • - Programming Interfaces - JDBC / ODBC / PHP / Perl / Phython / C / C++
  • Support for a wide range of data types - from basic data types like CHAR, VARCHAR, TEXT, INT, BLOB, CLOB, and URL
  • to user-defined data types
  • Partitioning - Horizontal and range partitions
  • File compression without a temporary need for available space, and encrypted backup and restoration
  • Runtime Processing - Explain, Trace, Debug, Prepare
  • Data Tampering Prevention - Grants read-only table property to users without permissions
  • Data Protection - Offers basic account management; records and controls data access and input/output behavior through process authentication
  • Column Encryption - Encrypts and stores by column (contains cryptographic verification module)
  • Operation Management - Text-based PetaSQL Client Tool and Orange for PetaSQL


  • Used as an operational configuration DB or a repository DB for various solutions
    • - Proved its quality and reliability through years of use as the operational and audit log repository for WareValley’s DB access control system
  • Offers easy usability by supporting the Orange for PetaSQL program

Support for Various Operating Environments

Windows FreeBSD Platform Linux UNIX
Supported Environments (Cloud)

Supported Specifications

Supported Specifications

Data Partitioning

  • Column Table
  • Range, Hash, List partition
NO Name Age
01 Kang 30
02 Kim 30
03 Lee 30
04 Song 30
05 Park 30

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
  • Processes multiple sessions simultaneously with threads
  • representative phone

  • Implementation and
    Technology Inquiries