MapReduce solutions

Platform MapReduce

Solutions

Next Generation MapReduce for Hadoop
Platform MapReduce Solutions for Big Data

Topics

MapReduce and the Big Data Challenge
MapReduce Use Cases
Deploying Hadoop in the Enterprise
Platform MapReduce Solution
News
Resources

MapReduce and the Big Data Challenge

Reporting and analysis drive businesses in making the best possible decisions. The source of all these decisions is data. With the explosion in data, capturing, managing and processing it at large scales has proved to be an issue using current tools and is referred to as the ‘Big Data’ challenge.

In order to process big data, new techniques are needed for both processing and storage of this data. The open source Hadoop stack has provided a paradigm shift for ‘Big Data’ management. By providing local computation and storage, the solution scales up from single servers to thousands of machines. Back to top

MapReduce Use Cases

MapReduce based distributed data processing is fast emerging as a high priority for businesses and government agencies that wish to harness the intelligence from big data. Early adopters span various industry verticals including financial services, government, retail, and life sciences. MapReduce application use cases that are ideal for Platform MapReduce in these vertical markets include:

Financial Services - Compliance and regulatory reporting, fraud detection and security analytics, credit scoring and analysis, and trade surveillance.
Telecommunications – Revenue assurance and price optimization, customer churn prevention, and call detail record (CDR) analysis.
Government Agencies – Fraud detection and cyber-security, compliance and regulatory analysis, and energy consumption and carbon footprint management.
Life Sciences – Drug discovery and development analysis, and genome sequencing analysis.
Retail – Customer data and buying patterns analysis, product recommendation engines.

Deploying Hadoop in the Enterprise

The open source Hadoop MapReduce has provided a paradigm shift for ‘Big Data’ management and analysis. However, it has a number of shortcomings which makes it hard for enterprises to deploy into production environments. The open source community has started to define the next generation architecture to address these problems.Platform Computing is delivering the next generation Hadoop MapReduce solution now, that aligns to the proposed architecture.

Top 5 Challenges of Hadoop MapReduce in the Enterprise
Rohit Valia, Director, HPC and Analytics Solutions

Platform MapReduce Solution

Platform Computing’s MapReduce solutions provide unique capabilities and are architected based on almost two decades of distributed computing research and development. Our distributed workload solutions provide for high scalability and fast performance through its low-latency distributed architecture while maintaining compatibility with Hadoop to leverage your IP investments. This solution maximizes the value of your information technology infrastructure by accelerating, sharing, and managing MapReduce applications efficiently.

The Platform MapReduce solution consists of:

Platform MapReduce product
Support for HDFS or other supported Distributed File Systems

Platform MapReduce delivers a robust architecture designed for high availability, utilization and throughput. It offers IT easy manageability and monitoring while providing sophisticated workload policies for multiple lines of business users and applications. Platform Computing also provides commercial support for the Hadoop Distributed File System (HDFS) when deployed with Platform MapReduce. In addition, customers can use Platform MapReduce with Appistry’s Cloud IQ or IBM GPFS.

Platform MapReduce is an enterprise-class product with support for Apache Hadoop MapReduce compatible programming model.

	Platform MapReduce Introduction Ken Hertlzer, VP Product Management and Marketing
	Platform MapReduce Technical Chalk Talk Scott Campbell, Director, Product Management