Blog Archives

The Problems that Scale-Out Architectures Create

Data intensive workloads like Elastic, Hadoop, Kafka and TensorFlow, are unpredictable, making it very difficult to design flexible storage architectures to support them. In most cases, scale-out architectures utilize direct attached storage (DAS). While DAS delivers excellent performance to the

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15 Minute Webinar: Composing Infrastructure for Elastic, Hadoop, Kafka and Cassandra to Drive Down Cloud Data Center Costs

Hyperscale applications like Elastic, Hadoop, Kafka and Cassandra typically use a shared nothing design where each node in the compute cluster operates on its data. Hyperscale architectures, to maximize storage IO performance, keep data local to the compute node processing

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Designing Storage for MongoDB, Spark, MySQL, and Cassandra – Pavilion Data Briefing Note

Modern applications like MongoDB, Spark, MySQL, and Cassandra are disrupting traditional storage architectures. To keep storage costs down and performance high these applications use direct attached PCIe flash storage. Many organizations are rapidly integrating NVMe. The problem is that direct-attached

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Dealing with the Storage Challenges Containers Create – Storidge Briefing Note

Containers have improved an organization’s ability to rapidly develop, test and deliver applications. In many cases however, storage is a boat anchor slowing the whole process down. As enterprises increase their use of container technology and begin using the technology

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Breaking Down Hadoop, Spark, Cassandra Silos – DriveScale Briefing Note

The storage architecture of most next generation applications, like Hadoop, Spark and Cassandra, leverage local, direct attached storage to avoid excessive storage traffic on the network and keep costs down. While this architecture does accomplish its goals, it also re-creates

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Enterprise Backup vs Point Backup

For two decades IT has had two choices when selecting a data protection solution. They can choose a holistic solution that covers the majority of the applications, operating systems and data protection goals or they can select a point data

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The Storage Challenges that Cassandra and Couchbase Create

Traditionally databases are scale up, running on a single powerful but expensive server. Distributed databases like Cassandra and Couchbase are scale-out and run on commodity white box servers, each of which becomes a node in a cluster. Traditional databases are

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Overcome Couchbase and Cassandra DRAM Aggravation

Couchbase and Cassandra count on the active data set to be in RAM. To overcome the RAM limits of a single server and to make more compute available, the environments run in a cluster that aggregates the RAM and CPU

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Posted in StorageShort