All Things Distributed

SEPTEMBER 20, 2013

Not everybody agreed that the "N-ary Storage Model" (NSM) was the best approach for all workloads but it stayed dominant until hardware constraints, especially on caches, forced the community to revisit some of the alternatives. A Decomposition Storage Model , George P. Copeland and Setrag N.

Storage 72

Storage Hardware Cache C++ 72

The Morning Paper

NOVEMBER 5, 2019

File systems unfit as distributed storage backends: lessons from 10 years of Ceph evolution Aghayev et al., In this case, the assumption that a distributed storage backend should clearly be layered on top of a local file system. What is a distributed storage backend? SOSP’19. This is not surprising in hindsight.

Storage 64

Storage Systems Hardware Efficiency 64

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 94

Hardware C++ Storage Cache 94

Scalegrid

JANUARY 5, 2024

The DBMS is key to maintaining these aspects by offering a storage system that allows users to perform operations such as data insertion, deletion, and selection, thereby promoting enhanced data integration across diverse applications and platforms. This is significant for modern business environments. <p>The </p>

Efficiency 147

Efficiency Storage Database Scalability 147

Scalegrid

JANUARY 25, 2024

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

Metrics 130

Metrics Monitoring Latency Cache 130

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

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

Highly Scalable

APRIL 2, 2012

The rationale behind these methods is that frontend should be able to fetch transient information very efficiently and separately from fetching of heavy-weight domain entities because this information cannot be cached. So, the only way was to cache all necessary data to minimize interaction with RDBMS.

Ecommerce 100

Ecommerce Cache Storage Architecture 100

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

Percona

JUNE 22, 2023

This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index. query cache: Disable (query_cache_size: 0, query_cache_type:OFF) innodb_adaptive_hash_index: Check adaptive hash index usage to determine its efficiency.

Performance 109

Performance Monitoring Traffic Database 109

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 164

Scalability Database Ecommerce Latency 164

ACM Sigarch

NOVEMBER 1, 2019

This blog post gives a glimpse of the computer systems research papers presented at the USENIX Annual Technical Conference (ATC) 2019, with an emphasis on systems that use new hardware architectures. GAIA proposed to expand the OS page cache into accelerator memory. Heterogeneous ISA. Programmable I/O Devices.

Architecture 12

Architecture Hardware Cache Storage 12

Scalegrid

JUNE 14, 2024

By utilizing query folding effectively, you can ensure that Power BI sends optimized queries to MySQL, which can take advantage of the database’s indexing, caching, and processing capabilities. It involves pushing as much of the data transformation and filtering operations back to the data source (e.g.,

Database 130

Database Azure Efficiency Servers 130

Brendan Gregg

FEBRUARY 28, 2023

Make sure your system can handle next-generation DRAM,” [link] Nov 2011 - [Hruska 12] Joel Hruska, “The future of CPU scaling: Exploring options on the cutting edge,” [link] Feb 2012 - [Gregg 13] Brendan Gregg, “Blazing Performance with Flame Graphs,” [link] 2013 - [Shimpi 13] Anand Lal Shimpi, “Seagate to Ship 5TB HDD in 2014 using Shingled Magnetic (..)

Performance 103

Performance Latency Cache Virtualization 103

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

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 95

Storage Mobile Website Java 95

SQL Performance

APRIL 27, 2020

The basic tier provides up to 5 DTUs with standard storage. The standard tier supports from 10 up to 3000 DTUs with standard storage and the premium tier supports 125 up to 4000 DTUs with premium storage, which is orders of magnitude faster than standard storage. New Hardware Configuration for Provisioned Compute Tier.

Azure 55

Azure Database Serverless Hardware 55

The Morning Paper

OCTOBER 4, 2020

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. Emerging architectures that shorten the path length, e.g. edge caching and computing, may also confine the latency. Application performance.

Energy 130

Energy Latency Performance Network 130

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 114

Availability Database Open Source Hardware 114

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. is access to hardware devices. This allows customisation and use of specialised features without custom, proprietary software for niche hardware.

Media 145

Media Games Education Engineering 145

Highly Scalable

SEPTEMBER 18, 2012

A database should accommodate itself to different data distributions, cluster topologies and hardware configurations. Permanent redirection means that the client is able to cache the mapping between the shard and the node. This redirect is a one-time and should not be cached. Data Placement. Davies, and T. Lakshman, P.Malik.

Database 213

Database Latency C++ Scalability 213

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

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. Hardware Past As Performance Prologue. The fastest Androids predictably remain 18-24 months behind, owing to cheapskate choices about cache sizing by Qualcomm, Samsung Semi, and all the rest.

Performance 127

Performance Network Metrics Cache 127

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. Delta implements the unified data management layer by extending the Amazon S3 object storage for ACID transactions and automatic data indexing.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

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 63

Benchmarking Open Source C++ Cache 63

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 storage, FIO is generally used. Storage: The system has a SATA drive for the operating system and one NVMe (Intel SSD D7-P5510 (3.84 Database: MySQL 8.0.31

Performance 55

Performance Benchmarking Cache Storage 55

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. What about security?

Hardware 56

Hardware Programming Media Storage 56

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. For single or very small numbers of predictions, Raven is faster due to SQL Server’s caching. The last word.

Processing 72

Processing Hardware Database Azure 72

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

n0derunner

DECEMBER 18, 2018

In our experiment we deliberately size the active working-set to NOT fit into the metadata cache. On the same hardware with AES enabled – the time is cut in half. Additionally AES reduces the need to cache metadata in DRAM since local access is so fast. For large datasets (e.g.

Performance 40

Performance Cache Hardware Storage 40

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

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. This not only results in cost savings by minimizing hardware requirements but also has the potential to decrease cloud expenses.

Tuning 52

Tuning Database Efficiency Performance 52

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 Ecommerce 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 Ecommerce 40

Highly Scalable

AUGUST 20, 2013

The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. In many cases join is performed on a finite time window or other type of buffer e.g. LFU cache that contains most frequent tuples in the stream. Interoperability with Hadoop.

Big Data 154

Big Data Processing Lambda Database 154

The Morning Paper

SEPTEMBER 19, 2019

Autoscaling tiered cloud storage in Anna. Could it be Analyzing efficient stream processing on modern hardware ? On one of the themes that captures my imagination, how changing hardware platform influence system design: Rethinking database high availability with RDMA networks. Research papers. (In In random order!).

Blockchain 46

Blockchain Hardware Google Speed 46