Percona

MARCH 27, 2023

Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. The percentage in degradation will vary depending on many factors {hardware, workload, number of tables, configuration, etc.}. Setup The setup consists of creating 10K tables with sysbench and adding 20 FKs to 20 tables.

Cache 106

Cache Hardware Servers Benchmarking 106

Percona

AUGUST 22, 2023

We’ll also look at the differences, as it’s important to know what architecture(s) will help you best meet your unique requirements for maximizing data assets and achieving continuous uptime. Redundancy: The system stores multiple copies of data on separate devices. there cannot be high availability.

Availability 82

Availability Hardware Open Source Database 82

Percona

SEPTEMBER 1, 2023

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. This not only enhances performance but also enables you to make more efficient use of your hardware resources, potentially resulting in cost savings on infrastructure.

Tuning 52

Tuning Database Performance Hardware 52

HammerDB

APRIL 19, 2023

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.

Performance 54

Performance Benchmarking Cache Storage 54

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. better cluster resource utilization.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Scalegrid

JULY 13, 2020

Oracle requires more complex ongoing administration, as all database configurations must evolve in conjunction with the data schemas and custom code. Scalability. PostgreSQL offers free scalability, and can scale up to millions of transactions per seconds. CitusDB – distributes data and queries horizontally across nodes.

Open Source 244

Open Source Tuning C++ Database 244

Percona

MAY 1, 2023

Key areas include: Configuration parameter tuning : This tuning involves altering variables such as memory allocation, disk I/O settings, and concurrent connections based on specific hardware and requirements. Slow queries and data retrieval can lead to frustrating delays that impact the user experience. Nobody has time for that!

Tuning 52

Tuning Efficiency Database Performance 52

HammerDB

FEBRUARY 25, 2021

HammerDB is a load testing and benchmarking application for relational databases. This helps to minimise locking allowing multiple sessions to access the same data at the same time. However, it is crucial that the benchmarking application does not have inherent bottlenecks that artificially limits the scalability of the database.

Programming 67

Programming Benchmarking Virtualization C++ 67

Percona

JULY 1, 2023

Understanding DBaaS DBaaS cloud services allow users to use databases without configuring physical hardware and infrastructure or installing software. These may be performance, high availability, operational cost, management, capacity planning, scalability, security, monitoring, etc.

AWS 52

AWS Database Serverless Storage 52

HammerDB

OCTOBER 12, 2018

As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. For anyone benchmarking MySQL with HammerDB it is important to understand the differences from sysbench workloads as HammerDB is targeted at a testing a different usage model from sysbench. large-pages.

Best Practices 40

Best Practices Scalability Performance C++ 40

Adrian Cockcroft

JUNE 21, 2022

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc.

Tuning 52

Tuning Benchmarking Engineering C++ 52

HammerDB

DECEMBER 5, 2020

A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint. better.

C++ 40

C++ Benchmarking Virtualization Open Source 40

Percona

AUGUST 30, 2018

Because recognizing if the workload is read intensive or write intensive will impact your hardware choices, database configuration as well as what techniques you can apply for performance optimization and scalability. Let’s examine the TPC-C Benchmark from this point of view, or more specifically its implementation in Sysbench.

Benchmarking 48

Benchmarking Database Operating System Architecture 48

KeyCDN

AUGUST 15, 2019

Before you begin tuning your website or application, you must first figure out which metrics matter most to your users and establish some achievable benchmarks. Quantitative performance testing looks at metrics like response time while qualitative testing is concerned with scalability, stability, and interoperability.

Testing Tools 55

Testing Tools Best Practices Performance Testing Testing 55

Percona

AUGUST 5, 2023

Partitioning is a way in which a database (MySQL in this case) splits its actual data down into separate tables but still gets treated as a single table by the SQL layer. Each partition holds data that falls within a specific range, optimizing data handling and query speed. Each type caters to different data distribution needs.

Strategy 40

Strategy Storage Database Best Practices 40

SQL Server According to Bob

SEPTEMBER 26, 2016

When we released Always On Availability Groups in SQL Server 2012 as a new and powerful way to achieve high availability, hardware environments included NUMA machines with low-end multi-core processors and SATA and SAN drives for storage (some SSDs). As we moved towards SQL Server 2014, the pace of hardware accelerated.

Availability 40

Availability Servers Hardware Benchmarking 40

VoltDB

JUNE 1, 2017

Hardware Optimizers” want to get the maximum utilization out of hardware. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. Attendees could be broken down into several distinct groups.

Hardware 56

Hardware Latency Virtualization Cloud 56

VoltDB

JUNE 1, 2017

Hardware Optimizers” want to get the maximum utilization out of hardware. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. Attendees could be broken down into several distinct groups.

Hardware 40

Hardware Latency Virtualization Cloud 40

SQL Server According to Bob

JANUARY 11, 2020

If ​​ it is ​​ not, ​​ the ​​ data ​​ is considered ​​ to be ​​ changed ​​ or ​​ damaged. In ​​ other words, ​​ a formula is applied ​​ to a given set of bytes.

Servers 40

Servers Cache Database Media 40

Smashing Magazine

JANUARY 6, 2020

It will help you build up a company-tailored case study with real data. Furthermore, using data from case studies and experiments published on WPO Stats will help increase sensitivity for business about why performance matters, and what impact it has on user experience and business metrics. Large preview ). Large preview ).

Performance 145

Performance Cache Network Metrics 145

Smashing Magazine

JANUARY 11, 2021

It will help you build up a company-tailored case study with real data. Furthermore, using data from case studies and experiments published on WPO Stats will help increase sensitivity for business about why performance matters, and what impact it has on user experience and business metrics. Large preview ). Large preview ).

Performance 145

Performance Cache Media Metrics 145

High Scalability

NOVEMBER 25, 2019

There are a couple of downsides though in case you are looking to use it to support tens of thousands of users working on hundreds of millions of files simultaneously containing petabytes of data. To help our customers manage ongoing data explosion, we have designed many of the core components over the last few years. Document store.

Architecture 52

Architecture Cache Azure Storage 52