Samsung Z-SSD and ScyllaDB: Delivering Low Latency and Multi-Terabyte Capacity in a Persistent Database
A Real-time, Low Latency, Key-Value Solution Combining Samsung Z-SSD™ and Levyx's Helium™ Data Store
Scaling In-Memory Data Processing with Samsung Advanced DRAM and NAND/SSD Solutions
High-Performance Workloads With Software-Defined Storage and NVMe SSDs
Enhancing the Value of Alluxio With Samsung NVMe SSDs
ScyllaDB and Samsung NVMe SSDs Accelerate NoSQL Database Performance
Performance and Endurance Enhancements with Multi-stream SSDs on Apache Cassandra
When using Samsung multistream-enabled 12G SAS SSD as backend storage for Cassandra, the primary benchmark findings are:
- Cassandra write performance improves up to 300%
- Cassandra average write latency decreases up to 67%
- SSD WA factor decreases up to 66%, enabling the SSD to last three times longer
Best Practices for MySQL with SSD
Scaling Cassandra Performance with Datera Elastic Data Fabric and Samsung SSDs
- Operational benefits with Datera EDF when deploying Apache Cassandra
- Performance comparison of deploying Apache Cassandra on Datera EDF versus deploying Apache Cassandra on direct-attached SSDs (server local)
- Ability to scale Apache Cassandra instances on Datera EDF
Accelerating OLTP performance with NVMe SSDs
Performance Benefits of Running RocksDB on SSDs
Data Center PCIe SSDs: Smart Choice Results in 5x Difference in Performance
Dell PowerEdge R930 with Oracle: The Benefits of Upgrading to Samsung NMVe PCIe Storage
NVMe SSDs and RDMA Deliver Hyperscale Performance – Windows Server 2012 SMB Direct Benchmark
Combined with Samsung's XS1715 SSDs and QLogic® FastLinQ 45000 Series 100GbE RDMA adapters, scale-out server configurations accessing networked storage systems can now exhibit unprecedented performance:
- More than 1 Million Storage Transactions per second
- More than 19 GB/s of data movement capabilities
NVMe SSDs and RDMA Deliver Hyperscale Performance – Linux iSEr Benchmark
Combined with Samsung's XS1715 SSDs and QLogic® FastLinQ 45000 Series 100GbE RDMA adapters, scale-out server configurations accessing networked storage systems can now exhibit unprecedented performance at low cost:
- More than 3 Million Storage Transactions per second
- More than 20 GB/s of data movement capabilities
Modeling Analytics for Computational Storage
NVMe-over-Fabrics Performance Characterization and the Path to Low-Overhead Flash Disaggregation
Storage disaggregation separates compute and storage to different nodes in order to allow for independent resource scaling and thus, better hardware resource utilization. While disaggregation of hard-drives storage is a common practice, NVMe-SSD (i.e., PCIe-based SSD) disaggregation is considered more challenging. This is because SSDs are significantly faster than hard drives, so the latency overheads (due to both network and CPU processing) as well as the extra compute cycles needed for the offloading stack become much more pronounced.
In this work we characterize the overheads of NVMe-SSD disaggregation. We show that NVMe-over-Fabrics (NVMf) - a recently-released remote storage protocol specification - reduces the overheads of remote access to a bare minimum, thus greatly increasing the cost-efficiency of Flash disaggregation. Specifically, while recent work showed that SSD storage disaggregation via iSCSI degrades application-level throughput by 20%, we report on negligible performance degradation with NVMf - both when using stress-tests as well as with a more-realistic KV-store workload.
Understanding performance of I/O intensive containerized applications for NVMe SSDs
Our cloud-based IT world is founded on hypervisors and containers. Containers are becoming an important cornerstone, which is increasingly used day-by-day. Among different available frameworks, docker has become one of the major adoptees to use containerized platform in data centers and enterprise servers, due to its ease of deploying and scaling. Further more, the performance benefits of a lightweight container platform can be leveraged even more with a fast back-end storage like high performance SSDs. However, increase in number of simultaneously operating docker containers may not guarantee an aggregated performance improvement due to saturation. Thus, understanding performance bottleneck in a multi-tenancy docker environment is critically important to maintain application level fairness and perform better resource management.
In this paper, we characterize the performance of persistent storage option (through data volume) for I/O intensive, dockerized applications. Our work investigates the impact on performance with increasing number of simultaneous docker containers in different workload environments. We provide, first of its kind study of I/O intensive containerized applications operating with NVMe SSDs. We show that 1) a six times better application throughput can be obtained, just by wise selection of number of containerized instances compared to single instance; and 2) for multiple application containers running simultaneously, an application throughput may degrade upto 50% compared to a stand-alone applications throughput, if good choice of application and workload is not made. We then propose novel design guidelines for an optimal and fair operation of both homogeneous and heterogeneous environments mixed with different applications and workloads.
Full Citation: http://ieeexplore.ieee.org/document/7820650/
System-Level Characterization of Datacenter Applications
This paper shows that for the purposes of designing an efficient datacenter, detailed microarchitectural characterization of "Big Data" applications is an overkill. It identifies four main system-level macro-architectural features and shows that these features are more representative of an application's system level behavior. To this end, a number of datacenter applications from a variety of benchmark suites are evaluated and classified into these previously identified macro-architectural features. Based on this analysis, the paper further shows that each application class will benefit from a very different server configuration leading to a highly efficient, cost-effective datacenter.
Performance Characterization of Hyperscale Applications on on NVMe SSDs
The storage subsystem has undergone tremendous innovation in order to keep up with the ever-increasing demand for throughput. NVMe based SSDs are the latest development in this domain, delivering unprecedented performance in terms of both latency and peak bandwidth. Given their superior performance, NVMe drives are expected to be particularly beneficial for I/O intensive applications in datacenter installations. In this paper we identify and analyze the different factors leading to the better performance of NVMe SSDs. Then, using databases as the prominent use-case, we show how these would translate into real-world benefits. We evaluate both a relational database (MySQL) and a NoSQL database (Cassandra) and demonstrate significant performance gains over best-in-class enterprise SATA SSDs: from 3.5 × for TPC-C and up to 8.5 × for Cassandra.
Performance analysis of NVMe SSDs and their implication on real world databases
The storage subsystem has undergone tremendous innovation in order to keep up with the ever-increasing demand for throughput. Non Volatile Memory Express (NVMe) based solid state devices are the latest development in this domain, delivering unprecedented performance in terms of latency and peak bandwidth. NVMe drives are expected to be particularly beneficial for I/O intensive applications, with databases being one of the prominent use-cases.
This paper provides the first, in-depth performance analysis of NVMe drives. Combining driver instrumentation with system monitoring tools, we present a breakdown of access times for I/O requests throughout the entire system. Furthermore, we present a detailed, quantitative analysis of all the factors contributing to the low-latency, high-throughput characteristics of NVMe drives, including the system software stack. Lastly, we characterize the performance of multiple cloud databases (both relational and NoSQL) on state-of-the-art NVMe drives, and compare that to their performance on enterprise-class SATA-based SSDs. We show that NVMe-backed database applications deliver up to 8x superior client-side performance over enterprise-class, SATAbased SSDs.