The Optimal Solution for Building and
Operating Your Big Data Systems

When it comes to Big Data Systems, EBIGs allows you to quickly resolve issues related to configuration, security, and operation.
Moreover, it minimizes the burden of system management by providing a consistent and secure platform for monitoring and
operating the Apache Hadoop Ecosystem.

  • System Configuration through Compatibility Verification

  • Operation Management Solution using Domestically Developed Technology

  • Effective Cost Savings

  • Provide Reliable Technical Support


EBIGs consist of an open-source Apache Hadoop ecosystem that has been built through self-compatibility verification, and a big data management platform that enables monitoring and operation.

  • Big Data System
    Configuration Management
    Hadoop cluster host
    and service management
  • Big Data System
    Setting Management
    Settings and history management
    by each service
  • Data Collection and Error Detection
    Workflow error detection
    and historical review
  • Hadoop Security Configuration
    Managing security policies
    through permission settings
  • Real-time Monitoring
    Real-time monitoring of
    Hadoop services and resources
  • HDFS Browsing
    big data directories and files
  • Hive Workspace
    Provide Hive database
    management and query editor
  • Status Alarm
    Service and threshold status alarms

Monitoring Views



This is a dedicated screen for the integrated monitoring of the Hadoop Cluster. EBIGs offers visualization for the Apache Hadoop EcoSystem, allowing users to monitor server, service, and node statuses while intuitively grasping key indicators of the Hadoop Cluster. Additionally, it provides a 3D dashboard for Hadoop Cluster Nodes.

· Resource/Node Manager, NameNode, HDFS, Hive, YARN, etc.

HDFS Monitoring

HDFS Monitoring

EBIGs provides dedicated HDFS monitoring, visualizing key indicators and performance metrics of the Hadoop Cluster. You can easily monitor Namenode's important metrics such as JVM Heap, GC, Active Namenode, HDFS Capacity, and Block Status. Additionally, HDFS Browser Audit allows users to trace and download work history.

Yarn Monitoring

Yarn Monitoring

Yarn Monitoring is useful when you want to understand key information such as summary and log about Yarn. EBIGs provides visualization for the performance and status of Hadoop Cluster, checks usage of Yarn Cluster, and displays execution history, making it easy to monitor applications.


Resource Monitoring

EBIGs maximizes resource availability by monitoring the real-time usage of various resources across the nodes that make up the Hadoop Cluster. All indicators of the Hadoop Cluster are collected in real-time, allowing you to easily check the current resource status.


Service List

EBIGs offers management capabilities for the Apache Hadoop ecosystem, allowing users to configure the system optimally by modifying and distributing the settings of each service. The web UI also provides access to execution history, making it easy to operate the ecosystem with its numerous installed services.

Analysis Views

Hive Editor

Hive Editor

EBIGs offers Hive Metastore for seamless data management. With Zeppelin, users can effortlessly utilize Hadoop data similar to RDBMS. You can manage and analyze tables and databases while conveniently visualizing inquiry data.

In-memory Analysis

In-memory Analysis

Spark-notebook accelerates analysis work by enabling data input from various sources and leveraging distributed processing in a cluster environment. EBIGs integrates Python with machine learning and graph algorithms for enhanced capabilities.


Customer Cases

  • Public

    Big Data Integration Platform

    Adoption Background

    There is a need for building a big data integration platform for economic revitalization and efficient data management and utilization.


    • Building big data platform infrastructure based on Apache Hadoop.

    • Success in building a data hub that provides integrated data on the region.

    • Provide services such as web and visualization by utilizing big data stored through EBIGs.

  • Electricity

    Power Disaster
    Recovery System

    Adoption Background

    Establishment of a future-oriented Disaster Recovery System (DRS) to secure business continuity for core business systems and configure a mutual backup system.


    • Building a disaster recovery system using EBIGs.

    • Configuration of real-time data replication environment that guarantees data integrity and consistency.

  • ICT

    Building a
    Master Platform

    Adoption Background

    Establishment of a system for efficient data management and analysis of each affiliate.


    • Building big data platform infrastructure based on Apache Hadoop.

    • Building data governance through data standardization.

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