Scylla Blog

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Posts with tag "Samsung"

Nov15

Honoring Our Users at the Scylla Summit

There’s nothing we enjoy more than seeing the creative and impressive things our users are doing with Scylla. With that in mind, we presented our Scylla User Awards at last week’s Scylla Summit, where we brought the winners up on stage for a big round of applause and bestowed them with commemorative trophies. I’m glad to share the winners here, along with a few notes on their use of Scylla. Most Interesting Technical Use Case: Nauto Nauto makes our roads safer. The company’s devices are deployed to fleet vehicles to monitor driver performance and help reduce risky behaviors. Nauto uses […]

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Apr17

Voice of Experience: Samsung SDS Chooses Scylla

samsung

Samsung SDS is a global IT services and solutions company with 57 offices spread across 31 countries. They are tasked with implementing highly performant and scalable systems for a number of Samsung businesses. However, they were experiencing a number of issues at the database layer. For example, their relational database couldn’t meet the performance requirements of several business use cases. As a result, they decided to conduct an in-depth technical evaluation of NoSQL databases.

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Mar13

Scylla on Samsung NVMe Z-SSDs

Organizations are continuing to adopt Solid State Drives (SSD) in their data centers for optimal performance and lower latencies. With that in mind, it only makes sense to use them with a database solution like Scylla to get the most bang for your buck. One of the popular SSD’s that organizations are adopting now in their data centers is the Samsung Z-SSD drive. In this post, we will go over the Z-SSD and see how Scylla users can benefit from the drives.

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Feb15

Scylla vs Apache Cassandra – Performance Benchmark by Samsung

Background Samsung MSL (Memory Solutions Lab) recently released benchmark results from a YCSB evaluation they conducted. We are thrilled to share Samsung’s results, which reiterate previous benchmark findings that Scylla performs 10X better than Apache Cassandra. If you have high-end hardware, you can expect the same results. On smaller machines, the difference is in the range of 1.5X to 3X. We recommend using larger machines to reduce both your node count and your Total Cost of Ownership.

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