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Customized
analysis environment supportCustomize and manage Hadoop ECO software composed of various and complex open source technologies according to customer's analysis requirements.
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High-speed storage processing
and real-time processing supportA distributed processing framework for large-scale data processing that allows distributed processing across multiple nodes, enabling fast data processing.
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Data distributed storage
for stabilityDistribute data across multiple nodes, replicate some of the data across nodes for increased reliability. Enables storage and access of large volumes of data.
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System operation support
Enables vendor-agnostic big data platform construction through pure open source Hadoop deployment, with a robust response system tailored to customer needs, resulting in a perfect system.
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Advanced pre-processing and real-time processing system
Realizes data processing without bottlenecks, from integrated data collection to processing, storage, analysis, utilization, and visualization.
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Web-based integrated big data analysis environment
Provides a web interface for visualizing and analyzing data, and enhances user convenience by providing various necessary tools and libraries via a web-based platform.
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Provisioning monitoring platform management function
Offers automatic provisioning and configuration of Hadoop clusters, and monitors their performance, availability, and stability, providing alerts to aid in fault response.
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Cost efficiency with open source
RNTire BDP is more cost-effective than existing commercial data processing solutions. Since it is based on open source, there are no license costs, and it can perform large-scale data processing without being constrained by hardware.
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Availability guarantee through distributed storage
RNTire BigData distributes data storage to enable data to be read from other nodes in case of errors in a single node, ensuring high availability.
- Web-based user interface
Provides an optimized work environment for various software executions through a web-based platform.
- Monitoring of H/W and S/W resources
By using the H/W and S/W resource statistical function, it is possible to check the analysis result of bottleneck and idle resources.
- Integrated Data Management
We provide a unified data environment and integrate research data for stability, usability, and convenience.
- S/W license management
You can manage and assign individual/departmental software licenses and monitor the overall application licenses for the system.
- Job scheduler
Slurm, a job scheduler based on Linux, is pre-installed by default.
- Configuration and management of specific resource groups
Various types of HPC resources (servers, VMs, GPUs, S/W, H/W, licenses) can be grouped and assigned to specific users and departments.
