Zettaset software manages the health, security and administration of your enterprise Hadoop environment.
Zettaset delivers a fault-tolerant and highly-available solution for massive data aggregation. Our Big Data solution is high performance, easy to deploy and has no single points of failure.
HIGHLIGHTS
• Point and click browser-based visual UI• Simple to deploy with no need for professional services• Automatic failover for NameNode, JobTracker and Oozie• Increased security with Kerberos authentication• Single administration management UI• Built-in automatic redundancy, monitoring, self-healing, and rapid-server provisioning• Simple licensing model• Supports trillions of files
Big data are large datasets, in the order of terabytes, exabytes and zettabytes. Working with this amount of data is challenging using existing databases and management tools when it comes to the analysis, volume, speed and diversity of the data. Bridging this gap allows analysts to make informed decisions, and as we enter the zettabyte age this becomes a necessity.
The Apache Hadoop software library framework allows for distributed processing of large datasets across clusters of computers on commodity hardware. This is most beneficial when combined with subprojects and other Hadoop-related projects. This solution is designed for flexibility and scalability, with an architecture that scales to thousands of servers. The library detects and handles failures at the application layer, delivering a high-availability service on commodity hardware.
Zettaset maximizes and enhances this offering by filling the gaps in the open-source projects, integrating as many as 30 services and dependencies into a single deployable system.
DEFINITIONS • Hadoop – Java software framework to support data intensive distributed applications
• ZooKeeper – a highly reliable distributed coordination system
• MapReduce – flexible parallel data processing framework on large datasets
• HDFS – Hadoop Distributed File System
• Oozie – a MapReduce job scheduler
• HBase – key-value database
• Hive – a high-level language built on top of MapReduce for analyzing large datasets
• Pig - enables the analysis of large datasets using Pig Latin. Pig Latin is a high-level language compiled into MapReduce for parallel data processing
• Admin Console / API – enables users to import, visualize, manipulate, analyze and export data with API support for almost all programming/scripting languages
• Services Management & Monitoring – automatic monitoring and restart of services
• High Availability – NameNode failover and services failover, no single point of failure
• Backups & Failover – hot Disaster Recovery (DR)
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