Percona

DECEMBER 14, 2022

In the database world there are essentially two types of database operations: Online Transaction Processing , OLTP : Online transaction processing applications have high throughput and are insert- or update-intensive in database management. Columnar storage. OLTP vs OLAP. Let’s get back to basics. consolidation (roll-up).

Database 91

Database Analytics Storage Processing 91

Dotcom-Montior

MAY 12, 2020

Websites are now more than just the storage and retrieval of information to present content to users. Database connectivity. Hardware resources. Database Connectivity. Present-day applications make more much use of the database. Hardware Resources. The list goes on and on. Connection time. Network latency.

Monitoring 63

Monitoring Entertainment Hardware Latency 63

The Morning Paper

SEPTEMBER 19, 2019

MongoDB is an important database, and this paper explains the tunable (per-operation) consistency models that MongoDB provides and how they are implemented under the covers. Microsoft have a paper describing their new recovery mechanism in Azure SQL Database , the key feature being that it can recovery in constant time.

Blockchain 46

Blockchain Hardware Google Analytics 46

SQL Server According to Bob

DECEMBER 18, 2018

Durability: “In database systems , durability is the ACID property which guarantees transactions that have committed will survive permanently. Microsoft SQL Server Database Engine Input/Output Requirements. Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system.

Servers 90

Servers Media Cache Storage 90

Percona

AUGUST 30, 2018

One of the common ways to classify database workloads is whether it is “read intensive” or “write intensive”. 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.

Benchmarking 47

Benchmarking Database Operating System Architecture 47

HammerDB

OCTOBER 12, 2018

Similarly for this guide MySQL can be swapped for a mySQL based databases such as MariaDB. As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. For this reason sysbench presents a vastly more simplified workload than HammerDB. . 10 rows in set (0.02

Best Practices 40

Best Practices Scalability Performance C++ 40

HammerDB

DECEMBER 5, 2020

A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. Why would this be the case?

C++ 40

C++ Benchmarking Virtualization Open Source 40

All Things Distributed

APRIL 5, 2012

One of the services that is very successful in driving innovation at our customers in this context is Amazon RDS , the Relational Database Service. Amazon RDS removes the headaches of running a relational database service reliably at scale, allowing Amazon RDS customers to focus on innovation for their customers. hands freeÃ?

Innovation 146

Innovation AWS Education Network 146

All Things Distributed

JULY 13, 2010

Additionally, many high-end HPC applications take advantage of knowing their in-house hardware platforms to achieve major speedup by exploiting the specific processor architecture. There is no more need for hardware tinkering to keep the clusters up and running (I spent many nights doing this; there is no glory in it). until today.

Cloud 118

Cloud AWS Automotive Latency 118

Smashing Magazine

JANUARY 15, 2019

The Green Web Foundation maintains an ever-growing database of web hosts who are either wholly powered by renewable energy or are at least committed to being carbon neutral. how much data does the browser have to download to display your website) and resource usage of the hardware serving and receiving the website.

Website Performance 74

Website Performance Website Energy Performance 74

Highly Scalable

AUGUST 20, 2013

This article is an effort to explore techniques used by developers of in-stream data processing systems, trace the connections of these techniques to massive batch processing and OLTP/OLAP databases, and discuss how one unified query engine can support in-stream, batch, and OLAP processing at the same time. Interoperability with Hadoop.

Big Data 154

Big Data Processing Lambda Database 154

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. Regardless, the overall story for hardware progress remains grim, particularly when we recall how long device replacement cycles are: Tap for a larger version.

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). With faster disks (i.e. AWS Aurora (based on MySQL 5.6)

Cache 46

Cache C++ AWS Airlines 46

All Things Distributed

OCTOBER 7, 2015

In AWS’ quest to enable the best data storage options for engineers, we have built several innovative database solutions like Amazon RDS, Amazon RDS for Aurora, Amazon DynamoDB, and Amazon Redshift. When you point QuickSight to a data source, data is automatically ingested into SPICE for optimal analytical query performance.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JANUARY 18, 2012

a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Today is a very exciting day as we release Amazon DynamoDB , a fast, highly reliable and cost-effective NoSQL database service designed for internet scale applications. Werner Vogels weblog on building scalable and robust distributed systems.

Scalability 167

Scalability Database Ecommerce Latency 167

Smashing Magazine

JANUARY 6, 2020

Study common complaints coming into customer service and sales team, study analytics for high bounce rates and conversion drops. Run performance experiments and measure outcomes — both on mobile and on desktop (for example, with Google Analytics ). Yet often, analytics alone doesn’t provide a complete picture.

Performance 145

Performance Cache Network Metrics 145

Smashing Magazine

JANUARY 7, 2019

To get accurate results and goals though, first study your analytics to see what your users are on. 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). You can then mimic the 90th percentile’s experience for testing.

Performance 104

Performance Cache Metrics Network 104

Abhishek Tiwari

DECEMBER 27, 2017

ETL is a product of the relational database era and it has not evolved much in last decade. 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. Leveraging the recent hardware advances.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

NOVEMBER 15, 2010

The early GPU systems were very vendor specific and mostly consisted of graphic operators implemented in hardware being able to operate on data streams in parallel. Programming the GPU evolved in a similar fashion; it started with the early APIs being mainly pass-through to the operations programmed in hardware. Syndication.

AWS 136

AWS Latency Programming Architecture 136

High Scalability

NOVEMBER 25, 2019

It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice.

Architecture 52

Architecture Cache Azure Storage 52