In this podcast, Jason Fedder, Ritu Kama, and Ted Willke from Intel describe the company’s new Intel Data Platform, a family of software for Big Data Analytics. “As big data shifts from hype to reality, Intel is helping to break down the barriers to adoption by easing complexity and creating more value,” said Boyd Davis, vice president and general manager of Intel’s Datacenter Software Division. “Much like an operating system for big data processing, the Intel Data Platform supports a wide variety of applications while providing improved security, reliability and peace of mind to customers using open source software.”
In this slidecast, Dev Patel and Poulomi Damany from BitYota describe the company’s Data Warehouse Service. “We are a Data Warehouse Service (DWS) available on major cloud providers like Rackspace and Amazon. We are designed from the ground up for high performance analytics on JSON data from fast-changing applications including web & mobile analytics and NoSQL stores like MongoDB. We don’t impact your operational store or app and best of all, as a fully managed service, we take the headache out of having to set up and manage another data platform.”
“GigaSpaces Technologies provides software middleware for deployment, management and scaling of mission-critical applications on cloud environments through two main product lines, XAP In-Memory Computing and Cloudify. Hundreds of Tier-1 organizations worldwide are leveraging GigaSpaces’ technology to enhance IT efficiency and performance, from top financial firms, e-commerce companies, online gaming providers, healthcare organizations and telecom carriers.”
“Altiscale offers the first cloud service purpose-built to run Apache Hadoop. We run the latest version of Hadoop on custom infrastructure, augmented with Apache Hive, Pig, and Oozie, and with first-class support for Python, R, and Ruby. Altiscale’s infrastructure is faster, more reliable, easier to use, and more affordable than alternatives.”
This probing panel discussion made available as an Alcatel-Lucent/NetApp sponsored webcast entitled: Big Data Big Problems How to Get the Most from Your Big Data Platform. The 43 minute video steps you through important aspects of how to approach a Big Data initiative for your organization.
Members of the Active Archive Alliance – including Crossroads, Fujifilm, QStar, SGI, and Spectra Logic – have compiled their top five predictions for data storage as it relates to active archives in the year to come.
“For customers who need to retain and access hundreds of terabytes of unstructured data, Quantum Lattus Object Storage is a self-healing, self-protecting private cloud solution that enables more efficient primary storage usage, delivers extreme archive data resiliency and protection, and offers low latency disk access to archive data. Compared to RAID or tape storage, Lattus Object Storage provides the most effective solution on a cost/performance basis for active access, retention and protection of unstructured data in large archive environments.”
“DataRPM is a revolutionary business intelligence and data analytics solution that provides a natural language question answering and search interface to analyze and visualize any data residing anywhere in corporate databases, big data systems, files, applications, 3rd party systems, data warehouses and even other business intelligence tools. Available on the cloud, on premises and embeddable in SaaS/ISV applications.”
“With data growing exponentially, one of the greatest data management challenges is end-to-end protection, governance, discovery and access, no matter the file type, device or social origination.” said Steve Duplessie, founder and senior analyst, Enterprise Strategy Group. “Tarmin’s latest release of GridBank is tailored to meet all the needs of organizations facing massive growth with unstructured data.”
“We developed H2O to unlock the predictive power of big data through better algorithms,” said SriSatish Ambati, CEO and co-founder of 0xdata. “H2O is simple, extensible and easy to use and deploy from R, Excel and Hadoop.”