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What is the problem that the Open Data Platform seeks to solve?

Last week, the Open Data Platform (ODP) was announced and written about in the technology and business press. While Altiscale has received strong support for its participation in the ODP, we have also received many questions about why the ODP is necessary and the exact role that it would serve. In this blog post, we want to explain more […]

By |February 24th, 2015|Hadoop, Spark|0 Comments|

Apache Spark Now on the Altiscale Data Platform

Apache Spark, the increasingly popular in-memory analytics platform, is now available on Altiscale’s Hadoop-as-a-Service (HaaS).

Spark is especially well suited for machine learning and other memory-intensive, iterative processes. Spark is increasingly used for stream processing as well. If you struggle with the latency encountered in many MapReduce jobs then consider using Spark in the Altiscale HaaS.  Spark employs a distributed […]

Altiscale Support Kerberos Authentication for Hadoop

Altiscale is now offering secure-mode Hadoop using Kerberos authentication.  Kerberos is well-known as a strong authentication mechanism, but it was designed for a client-server environment, not the highly dynamic and scalable Hadoop environment. As a result, many Hadoop clusters are not running  in secure mode. This is a problem.

Without an authentication mechanism such as Kerberos, there is no way […]

The Open Data Platform: Uniting for an Enterprise-Class Hadoop Ecosystem

This morning, a coalition of fourteen leading technology organizations announced the creation of the Open Data Platform (ODP), an industry association dedicated to accelerating the adoption of enterprise-class, big data applications that are based on the Apache Hadoop ecosystem of solutions. We at Altiscale are proud to be part of this initiative.

One of my roles at Yahoo! was to […]

The Total Economic Impact™ Of Altiscale Hadoop-as-a-Service: Cost Savings And Business Benefits Enabled By Hadoop-as-a-Service

Altiscale commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying its Hadoop-as-a-Service (HaaS). The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Altiscale’s Hadoop-as-a-Service on their organizations.

To better understand the benefits, costs, and risks […]

By |February 11th, 2015|Big Data, Hadoop|0 Comments|

Tips for building a Data Science Platform

Heading to Strata+Hadoop World next week? Come see our very own Dr. David Chaiken present at the Big Data Science @ Strata Meetup on Tuesday, February 17th at 5;30pm. The Meetup will take place at the San Jose Convention Center, Room 210AE.

David’s Talk:

In attempting to use Hadoop-based data, data scientists face two bad options:  use Hadoop indirectly by using […]

Spark and Hadoop Together in the Cloud

When it comes to running Spark and Hadoop in the cloud, Altiscale provides the best of both worlds. As an example, our cloud platform utilizes YARN for resource management. This means you can leverage MapReduce for large-scale batch processing while opting to deploy Spark for in-memory, interactive analysis using GraphX, MLLib, or your own custom Spark applications.

Altiscale supports Spark […]

By |February 3rd, 2015|Hadoop, HDFS, Spark, YARN|0 Comments|

Security Needs to be Demonstrated

Altiscale was founded to bring Hadoop to the enterprise through the Cloud. Most of us come from large Web companies like Yahoo!, Google and LinkedIn. We bring with us a very deep understanding of the technical aspects of cloud security issues and the practical experience of dealing with security threats, ranging from teenage hackers to foreign governments.

One important lesson […]

Computer Security Alliance Provides Needed Big Data Taxonomy

If you’ve ever had to explain big data to non-IT professionals, you will appreciate the efforts of the Computer Security Alliance’s Big Data Working Group. They have published a Big Data Taxonomy.

The taxonomy is organized around six key areas: data, compute infrastructure, storage infrastructure, analytics, visualization, and security and privacy. The working group defined hierarchies of elements within each […]

By |January 15th, 2015|Big Data, Hadoop|0 Comments|

Data Gravity? Not so much!

As a vendor of “Big Data in the Cloud,” we often get asked about data “gravity,” i.e., the challenges that arise when moving large amounts of data around in the cloud. A common assumption behind these questions is that big-data infrastructure needs to be co-located with big-data sources.

The fact is data has less gravity than is typically believed. This […]

By |January 13th, 2015|Big Data, Hadoop|0 Comments|