Scylla Blog

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Posts with tag "ssd"

Feb25

In-Memory Scylla, or Racing the Red Queen

Racing the Red Queen

“Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” — The Red Queen to Alice, Alice Through the Looking Glass In the world of Big Data, if you are not constantly evolving you are already falling behind. This is at the heart of the Red Queen syndrome, which was first applied to the evolution of natural systems. It applies just as much to the evolution of technology. ‘Now! Now!’ cried the Queen. ‘Faster! Faster!’ […]

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May18

Ola Cabs on Their First Two Years of Using Scylla in Production

Ola Cab image

Ola Cabs shares their two-year journey with Scylla and how it lived up to their expectations. Learn how they graduated from using Scylla for very simple and non-critical use cases to running it for their mission-critical flows.

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May2

Intel’s Memory Group on the Advantages of Scylla

intel

The Intel Memory Group is behind the revolutionary Optane SSD drive that provides breakthrough performance and is 5-8x faster at Low Queue Depths than traditional SSD’s. Intel began working with ScyllaDB staff last year to build a big memory system at high-volume scale. They chose Scylla because they needed a solution that can fully leverage the hardware to derive the best possible performance.

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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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Dec6

Intel Optane and Scylla: In-memory Performance at a Lower Cost

optane

Solving your performance problems with Intel Optane Organizations often face problems with their current database infrastructure regarding performance, data persistence, and cost. Some may use in-memory databases to help address performance concerns but they may run into data persistence issues. Sacrificing the integrity of your data is never a good tradeoff for performance. Also, more memory in a server will drive up costs. An ideal solution would provide the performance of an in-memory database without compromises on throughput, latency, and data persistence.

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