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Tag: Mesos

Containerized Spark Deployment Pays Dividends

Hadoop has emerged as a general purpose big data operating system that can perform a range of tasks and run all kinds of processing engines. But all that power and flexibility comes with a cost, which is something that o Read more…

Concord Claims 10x Performance Edge on Spark Streaming

Organizations that are looking for a stream processing engine upon which to build fast data applications featuring high-throughput and low-latency may want to check out Concord, a new framework that emerged from the ad-t Read more…

Alliance Coalesces Around Mesosphere Platform

The datacenter operating system movement continues to gather momentum with the announcement by Apache Mesos developer Mesosphere of a broad alliance backing the beta release of an all-encompassing platform for building a Read more…

From Hadoop to Zeta: Inside MapR’s Convergence Conversion

If you're a regular Datanami reader, you likely know MapR Technologies as a Hadoop distributor, one of the three "pure play" providers alongside Hortonworks and Cloudera. But with its integrated NoSQL database, a modifie Read more…

Teradata Puts Aster in Hadoop for IoT Analytics

The Internet of Things (IoT) is simultaneously a colossal data management challenge and the analytic opportunity of a lifetime. Teradata (NYSE: TDC) addressed both of those today with two product announcements, including Read more…

Riak Taps Mesos for ‘Push Button’ NoSQL Scalability

At the MesosCon conference this week, Basho Technologies and Cisco are demonstrating the Riak key-value store database running atop Apache Mesos, the next-gen cluster manager developed by UC Berkeley's AMPLab. As Basho C Read more…

Project Myriad Brings Hadoop Closer to Mesos

One of the challenges of running Hadoop is resource management. The process of spinning up and managing hundreds, if not tens of thousands, of server nodes in a Hadoop cluster—and spinning them down and moving them, et Read more…

The Art of Scheduling in Big Data Infrastructures Today

Arun Murthy, architect with Hortonworks, said recently that the Hadoop community wanted to “fundamentally re-architect Hadoop...in a way where multiple types of applications can operate efficiently and predictable within the same cluster”. The starting point to do this, he says, is YARN, which has the potential to “turn Hadoop from a single application system to a multi-application operating system”. Fritz Ferstl, CTO with Univa argues that such efforts may run the risk of reinventing the wheel. Read more…

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