Kick start Hadoop with right platformExclusively suited for Hadoop's multi server deployments
With data storage and high-performance parallel data processing
IRON Global Big Data Appliance HDPOD is a comprehensive Hadoop Big Data platform, engineered for reliable data processing with a low overall total cost of ownership. The HDPOD combines network, server and storage hardware, and the comprehensive Hortonworks Data Platform (HDP) software suite into an optimized turnkey configuration. This creates a complete single SKU solution with integrated hardware, software and support services that is simple to acquire and deploy.
The HDPOD Appliance for Hadoop with Hortonworks Data Platform is built using industry-standard commodity hardware and offers low cost, fast performance with the latest generation of Intel technology combined with a fabric-based hardware configuration for enterprise-class data storage and management. The HDPOD appliance platform helps enterprises derive value almost instantly with low project risk and cost by providing a single platform for multi-workload data processing across an array of processing methods, from batch through interactive to real-time - all supported with solutions for governance, integration, security and operations.
Apache Hadoop is a core component of the modern data architecture, integrating with and complementing your existing systems to create a highly efficient, highly scalable way to manage all your enterprise data. HDP's modern data architecture provides the foundation for your own enterprise Data Lake, which is an integral part of your business strategy for unleashing analytic insights and innovations that help you compete and win in today’s marketplace. HDPOD platforms provides analysts the ability to leverage valuable customer insights (across all channels; web, mobile, social media, email, contact center, database, and storefront, and other type of customer interaction data) in their analysis while using familiar tools.
Accelerate the journey to big data using simple, efficient, flexible and open architecture IRON Global offers enterprise and service provider system designs that are reliable and energy-efficient, coupled with simplified serviceability and deployment services. Our solutions with power efficient design, high density configurations and leading-edge management software help organizations manage the modern data center and benefit from cloud and big data computing-faster and easier.
HDPOD is pre-configured and pre-integrated to achieve better results:
Hadoop deployments require customers to acquire hardware to specific configurations, racking and configuring the hardware, operating system deployments and configurations, and installation of a huge set of Hadoop software packages with hundreds of pre-requisite packages. These deployments typically require several weeks to months of development cycle.
IRON HDPOD Big Data Appliance is designed to be a Hortonworks Data Platform (HDP) powered Hadoop Proof-of-Concept (POC) platform for running enterprise data analytics environments. It is a complete Hadoop Big Data environment which helps validate big data for target business and boot straps project for a small price tag, sold as a single SKU. It is simple to install as a PC for a very small cost-> plug into the corporate network directly, power up and it is ready to use immediately.
With ~100 (300 max) terabytes of storage, and 10 (2+8) nodes cluster, the HDPOD is powerful enough to be a full-fledged data analytics platform for any enterprise; customers can realize an ROI with the first few jobs. HDPOD can be used for testing, training, and later for production as-is or migrated to larger hardware platforms as desired.
IRON HDPOD is designed to be a Hortonworks Hardoop HDFS powered Big Data storage platform for running enterprise data analytics environments, the design offers:
Hardware Components & Specifications | H220SH | H320SF | H320S-P2 | H320-P4 | |
Network Fabric | |||||
• Aggregate/ Data Storage Switch: | 1U, 36x 40/56GbE QSFP Ports Ethernet Switch | 2 | 2 | 4 | 8 |
• Management Switch: | 1U, 44x 1GbE RJ45, 4x SFP Ports Ethernet Switch | 1 | 1 | 2 | 4 |
Cluster Management Server Appliance | |||||
• Management Node Server: | 1U, IRON iServer Single Node, 2x 10GbE & 1-IPMI Ports | 1 | 1 | 1 | 1 |
Name Nodes for Hadoop | |||||
• Nodes (Master Server) | 2U, IRON iServer Single Node, 2x 10GbE & 1-IPMI Ports | 3 | 3 | 3 | 3 |
• CPU: | Intel Dual Socket, 12 Core, 2.6Ghz CPU (Total 24 Cores/Node) | ||||
• Memory (GB): | 96, 128, 192, 256, 384 & 512 Options (256GB default) | ||||
• Disk Drives | Number of Disks – 10x; 900GB 10K RPM (per Node) | ||||
Three nodes: 1x Primary named node, 1x Secondary named nodes (+HBase Master, Hive Server), 1x Job Tracker node | |||||
Data Storage Nodes for Hadoop HDFS | |||||
• Blade Enclosures: | 4U, IRON iServer, Quad Node Blade Chassis (4 blades) | 4 | 8 | 17 | 24 |
• Nodes ( Server Blades): | 4 Server Nodes/Chassis, 2x 40Gbe LAN & 1-IPMI Ports | 16 | 32 | 68 | 140 |
• Processors (CPU/Cores): | Dual Socket, 6 Core, 2.0Ghz CPU (Total 12 Cores/Blade) | 32/192 | 64/384 | 136/816 | 280/1,680 |
• Memory (GB): | 96, 128, 192, 256, 384 & 512 Options (128GB default) | 2,048 | 4,096 | 8,704 | 17,920 |
• Disk Drives | Number of Disks – 6,8 or 12 per Node (6 default) | 96 | 192 | 408 | 840 |
Total Disk Capacity (Raw*) | 1TB, 2TB, 3TB & 6TB SAS (4TB default) | 384 | 768 | 1,632 | 3,360 |
*Capacities listed uncompressed (3x compression assumed typical) without Compression | |||||
Total Disk Capacity (Usable) | Usable mirrored capacity (appr.) | 192 | 384 | 816 | 1,680 |
Total Disk Capacity (Usable) | Usable Triple mirrored capacity (appr.) | 128 | 256 | 644 | 1,120 |
Additional Hardware and Software | |||||
• Rack | IRON 42U Rack, Redundant PDUs | 1 | 1 | 2 | 4 |
• KVM | IRON Keyboard/Mouse/Video Display Console, Optional | ||||
• Software (System) | Linux Operating System, 64bit | ||||
Microsoft Windows Server 2012 R2 Optional | |||||
• Software (Add-On), Optional | Data Protection for Volume & MapReduce layers | ||||
Dynamic Data Set management, metadata, and data lineage | |||||