We are excited to host our third annual Scylla Summit this year, and we would love to see you there. We had a very successful summit last year. Our growing community had the opportunity to hear firsthand from Scylla users about their success and also from our engineers about the underlying architecture that enables us to deliver predictable low latencies at high throughput out of the box. What’s coming on our product roadmap? We’ll talk about that too! Just in case you’d to see the kind of content we had at last year’s Summit, we’ve made the recordings available […]
Explore the main differences between i3.16xlarge in the i3 family and i3.metal on AWS. Will removing the virtualization layer bring better performance?
Learn how Scylla leverages control theory to keep compactions under control. We’ll discuss the approach ScyllaDB prescribes for solving this problem.
One of the cornerstones of Scylla is the I/O Scheduler, described in details at the moment of its inception in a two-part series that can be found here (part 1) and here (part 2). In the two years in which Scylla has been powering mission-critical workloads in production the importance of the I/O Scheduler was solidified and as our users have attested themselves, it plays a key part in isolating workloads and delivering on our Autonomous Operations promise.
As most earthlings are aware by now, two severe attacks under the names of Meltdown and Spectre were currently disclosed and it affects pretty much everybody living in modern society. Although there is no defense against the more elaborate Spectre, there is a software defense against the more widespread Meltdown. However, there is a catch that set the Internet on fire over the past few days. To protect oneself against Meltdown brings with it a performance penalty of up to 30%.
For a long time, permanent storage has been the bottleneck in most computer systems. Scylla operates under that assumption and includes a fully-featured userspace disk I/O Scheduler that is used to guarantee that different tasks in the database get their fair share of the disk. The I/O Scheduler is the central component at the heart of Scylla’s workload conditioning promise: to automatically adjust the database’s distribution of requests to adapt to the incoming workload. It is capable of providing Quality-of-Service (QoS) among the various tasks in the database and isolating them from each other. Since database systems tend to be […]
By default, Scylla SSTables will be compressed when they are written to disk. As mandated by the file format, data is compressed in chunks of a certain size – 4kB if not explicitly set. The size of the chunk is one of the parameters for the compression property to be set at table creation. Chunk-based compression presents trade-offs that users may not be aware of. In this post, I will try to explore what those trade-offs are and how to set them correctly for maximum benefit. As trade-offs imply different results for different loads, we will focus on single-partition read […]
Amazon recently unveiled a new class of machines—the AWS i3 family. Targeted at I/O intensive applications and featuring up to 15TB of fast storage, these machines offer unprecedented power with a great balance between I/O and CPU. At a lower price than the previous i2 family, we expect the i3 family to become the default class for NoSQL workloads. This article will cover i3 instances and provide information about the status of Scylla support for the hardware. Although we don’t yet officially provide i3 AMIs, customers are already running them in production with positive results. Scylla’s native architecture takes advantage […]
What to expect from Scylla’s performance on low-end hardware Scylla is a reimplementation of Apache Cassandra that has been demonstrated by us and third parties to perform up to 10x better than Apache Cassandra. These performance advantages stem from Scylla’s modern hardware-friendly and ultra-scalable architecture. As a result, Scylla’s performance grows as the hardware size grows. Scaling both up and out offers many advantages: from simplified cluster management to access to generally better hardware and economies of scale. We will address those choices in detail in an upcoming blog post. However, many users have compelling reasons to stay on low-end hardware, […]
What is Workload Conditioning? What is the best request rate I should throw at my cluster? What disk bandwidth should I make available for compactions? How many reader or writer threads should I have? What are the best size for my memtables?