HammerDB

APRIL 19, 2023

As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components. For example, if you are buying the latest Amazon memory-optimized EC2 instance (R7iz), the AWS page ( [link] ) tells us the following: Up to 3.9 Be sure to check back.

Performance 54

Performance Benchmarking Cache Storage 54

Smashing Magazine

JUNE 18, 2020

More specifically, we’re going to talk about storage and UI differences, which are the ones that most often cause confusion to developers when writing Flutter code that they want to be cross-platform. Example 1: Storage. Secure Storage On Mobile. The situation when it comes to mobile apps is completely different.

Storage 93

Storage Mobile Website Java 93

The Morning Paper

OCTOBER 4, 2020

There are high hopes for 5G , for example unlocking new applications in UHD streaming and VR, and machine-to-machine communication in IoT. Three different 5G phones are used, including a ZTE Axon10 Pro with powerful communication (SDX 50 5G modem) and compute (Qualcomm Snapdragon TM855) capabilities together with 256GB of storage.

Energy 130

Energy Latency Performance Network 130

Percona

MARCH 23, 2023

Hardware Memory The amount of RAM to be provisioned for database servers can vary greatly depending on the size of the database and the specific requirements of the company. By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way.

Performance 127

Performance Hardware Tuning Storage 127

ScaleOut Software

APRIL 22, 2020

The Solution: Distributed Caching. The solution to this challenge is to use scalable, memory-based data storage for fast-changing data so that web sites can keep up with exploding workloads. It’s not enough simply to lash together a set of servers hosting a collection of in-memory caches.

Cache 52

Cache Storage Servers Database 52

ScaleOut Software

APRIL 22, 2020

The Solution: Distributed Caching. The solution to this challenge is to use scalable, memory-based data storage for fast-changing data so that web sites can keep up with exploding workloads. It’s not enough simply to lash together a set of servers hosting a collection of in-memory caches.

Cache 52

Cache Storage Servers Database 52

Smashing Magazine

JANUARY 15, 2019

how much data does the browser have to download to display your website) and resource usage of the hardware serving and receiving the website. An obvious metric here is CPU usage, but memory usage and other forms of data storage also play their part. For example, what actually deserves or needs to be on a homepage?

Website Performance 73

Website Performance Website Energy Performance 73

Percona

MARCH 28, 2023

” This acts as a step to ensure durability by recovering lost data from the same journal files in case of crashes, power, and hardware failures between the checkpoints (see below) Here’s what the process looks like. The same data, in the form of pages inside the Wiredtiger cache, are also marked dirty. wt and index-*.wt).

Hardware 89

Hardware C++ Storage Cache 89

ACM Sigarch

NOVEMBER 4, 2019

Krste Asanovic from UC Berkeley kicked off the main program sharing his experience on “ Rejuvenating Computer Architecture Research with Open-Source Hardware ”. He ended the keynote with a call to action for open hardware and tools to start the next wave of computing innovation. This year’s MICRO had three inspiring keynote talks.

Hardware 18

Hardware Architecture Programming Innovation 18

Scalegrid

DECEMBER 21, 2023

To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. Advanced monitoring techniques enable you to identify potential issues, such as high latency, CPU utilization, command throughput, and cache hit rate before they become major problems.

Strategy 130

Strategy Monitoring Latency DevOps 130

The Netflix TechBlog

MARCH 8, 2021

They need specialized hardware, access to petabytes of images, and digital content creation applications with controlled licenses. They could need a GPU when doing graphics-intensive work or extra large storage to handle file management. Instead, we created a service to take the most popular configurations and cache them.

Entertainment 306

Entertainment Storage Hardware Open Source 306

The Netflix TechBlog

NOVEMBER 15, 2022

But it’s not easy: to pull this off, VFX studios need to build and operate serious technical infrastructure (compute, storage, networking, and software licensing), otherwise known as a “ render farm.” This program is just one example of the many ways Netflix strives to entertain the world.

Cloud 282

Cloud Entertainment AWS Infrastructure 282

SQL Server According to Bob

DECEMBER 18, 2018

For example, if a flight booking reports that a seat has successfully been booked, then the seat will remain booked even if the system crashes.” – [link]. Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system. Any storage device that can survive a power outage.

Servers 90

Servers Media Cache Storage 90

Highly Scalable

AUGUST 20, 2013

The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Consider an example where the data is grouped by a string key and sum of the numerical values is computed in each group: In this example, computation consists of two steps: local aggregation and global aggregation.

Big Data 154

Big Data Processing Lambda Database 154

HammerDB

JUNE 27, 2022

It enables the user to measure database performance and make comparative judgements about database hardware and software. These factors meant that often when looking for database performance information, the results for a particular combination of software and hardware were not available. Cached vs Scaled Workloads.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

SQL Server According to Bob

JANUARY 11, 2020

Stable Media Stable media is often confused with physical storage. SQL Server defines stable media as storage that can survive system restart or common failure. Stable media is commonly physical disk storage, but other devices and certain caching facilities qualify as well.

Servers 40

Servers Cache Media Hardware 40

The Morning Paper

DECEMBER 8, 2019

Byte-addressable non-volatile memory,) NVM will fundamentally change the way hardware interacts, the way operating systems are designed, and the way applications operate on data. The beauty of persistent memory is that we can use memory layouts for persistent data (with some considerations for volatile caches etc.

Hardware 56

Hardware Programming Media Storage 56

SQL Performance

DECEMBER 17, 2019

This removes the burden of purchasing and maintaining your hardware, storage and networking infrastructure, while still giving you a very familiar experience with Windows and SQL Server itself. There are also large differences in storage capacity and throughput between these extremes. GHz, 128MB of L3 cache, 128 PCIe 4.0

Azure 72

Azure Virtualization Servers Storage 72

Percona

JUNE 22, 2023

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. If a primary server fails, a backup server can take over and continue to serve requests.

Availability 109

Availability Database Open Source Hardware 109

Percona

APRIL 17, 2023

For example, on a 128GB memory host, this can allow up to 38.4GB of dirty pages. Make sure the drives are mounted with noatime and also if the drives are behind a RAID controller with appropriate battery-backed cache. The background ratio won’t kick in until 12.8GB. By default, it uses 50% of the memory + 1 GB.

Best Practices 52

Best Practices Design Tuning Database 52

The Morning Paper

FEBRUARY 20, 2020

… based on interactions with enterprise customers, we expect that storage and inference of ML models will be subject to the same scrutiny and performance requirements of sensitive/mission-critical operational data. statement adds the source code for the model pipeline (Python in the example) to the database. An INSERT INTO model.

Processing 72

Processing Hardware Database Azure 72

Highly Scalable

APRIL 2, 2012

I cannot disclose customer’s name, so I will explain business logic using amazon.com as an example, fortunately the basic functionality is very similar. For example, if the user opens a category that contains clothes, products will be characterized by properties like size, brand, color and so on.

Ecommerce 100

Ecommerce Cache Storage Architecture 100

Alex Russell

APRIL 29, 2021

Chrome has missed several APIs for 3+ years: Storage Access API. An extension to Service Workers that enables browsers to present users with cached content when offline. A tool for reliably sending data — for example, chat and email messages — in the face of intermittent network connections. is access to hardware devices.

Media 145

Media Games Education Engineering 145

The Morning Paper

MARCH 17, 2020

Optane DIMMs have lower latency and higher bandwidth than storage devices connected over PCIe (including Optane SSDs), and present a memory address-based interface as opposed to a block-based NVMe interface. Use non-temporal stores for large transfers, and control cache evictions. Optane DIMMs are here! to 0.98.

Scalability 59

Scalability Latency Cache Media 59

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

SQL Server According to Bob

JANUARY 11, 2020

As ​​ a ​​ simple ​​ example, ​​ take the following ​​ 2-byte string value of “AB” and apply a formula to it (Value = Position + ASCII value). ​​ Checksum ​​ is ​​ the sum of the values.

Servers 40

Servers Cache Database Media 40

Abhishek Tiwari

DECEMBER 27, 2017

More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues. Databricks Delta is a perfect example of this class. Leveraging the recent hardware advances. Overall, less complexity to deal with.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Morning Paper

APRIL 2, 2019

In this context it means there are no external dependencies on e.g. secrets, trusted hardware modules, or special instructions (e.g. TPMs, SGX, …), and no polynomial bounds on an adversaries computing power (so for example they still work even in a post-quantum world). Proof in appendix B of the accompanying technical report).

Software 40

Software Software Programming Hardware 40

Alex Russell

MARCH 6, 2021

A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. The Moto G4 , for example. Hardware Past As Performance Prologue. But the hardware future is not evenly distributed, and web workloads aren't heavily parallel. Mind The Gap.

Performance 124

Performance Network Cache Metrics 124

Percona

JANUARY 17, 2019

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. now has a version which will support parallelism for SELECT queries (utilizing the read capacity of storage nodes underneath the Aurora cluster). The second and third run used the cached data.

Cache 47

Cache C++ AWS Airlines 47

Highly Scalable

SEPTEMBER 18, 2012

A database should accommodate itself to different data distributions, cluster topologies and hardware configurations. This approach is used for example in Cassandra. This behavior can be semantically inappropriate (for example, if both clients add a value to a list). In this example R=2, W=2, N=3. Data Placement.

Database 213

Database Latency C++ Scalability 213

All Things Distributed

JANUARY 18, 2012

In response, we began to develop a collection of storage and database technologies to address the demanding scalability and reliability requirements of the Amazon.com ecommerce platform. s pricing is simple and predictable: Storage is $1 per GB per month. The growth of Amazonâ??s Domain scaling limitations. Amazon DynamoDBâ??s

Scalability 167

Scalability Database Ecommerce Latency 167

Alex Russell

OCTOBER 22, 2017

If our example document wasn’t reliant on JavaScript to construct the <my-app> custom element, the contents of the document would likely be interactive as soon as enough CSS and content was available to render meaningfully. Time required to read bytes from disk (it’s not zero, even on flash-based storage!).

Performance 68

Performance Benchmarking Network Mobile 68

Smashing Magazine

JANUARY 11, 2021

Build Optimizations JavaScript modules, module/nomodule pattern, tree-shaking, code-splitting, scope-hoisting, Webpack, differential serving, web worker, WebAssembly, JavaScript bundles, React, SPA, partial hydration, import on interaction, 3rd-parties, cache. Adjust the argument depending on the group of stakeholders you are speaking to.

Performance 145

Performance Cache Media Metrics 145

Smashing Magazine

JANUARY 6, 2020

Run performance experiments and measure outcomes — both on mobile and on desktop (for example, with Google Analytics ). Rather than focusing on full page loading time (via onLoad and DOMContentLoaded timings, for example), prioritize page loading as perceived by your customers. What does it mean? Large preview ).

Performance 145

Performance Cache Network Metrics 145

Smashing Magazine

JANUARY 7, 2019

One way or another, rather than focusing on full page loading time (via onLoad and DOMContentLoaded timings, for example), prioritize page loading as perceived by your customers. On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later).

Performance 103

Performance Cache Metrics Network 103