Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. What are the key advantages of DBMS?

Efficiency 147

Efficiency Storage Database Scalability 147

The Morning Paper

JUNE 25, 2019

Designing far memory data structures: think outside the box Aguilera et al., Last time out we looked at some of the trade-offs between RInKs and LInKs , and the advantages of local in-memory data structures. For many data center applications this looks to me like it could be a compelling future choice. HotOS’19.

Design 80

Design Cache Hardware Scalability 80

Speed Curve

FEBRUARY 10, 2025

Older hardware If you subscribe to faster service through your ISP, but you're using an older modem and/or an older router, you may not be getting the service you're paying for. For a myriad of reasons, older hardware can't always accommodate faster speeds. Most people use the same hardware for between five to ten years.

Hardware 52

Hardware Internet Internet Speed 52

Percona

MARCH 27, 2023

The percentage in degradation will vary depending on many factors {hardware, workload, number of tables, configuration, etc.}. having to open each table.frm (and in which my test runs, I have purposely read a very high number of tables compared to “Table-open-cache” variable). Results for Percona Server for MySQL 8.0

Cache 124

Cache Hardware Servers Benchmarking 124

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 144

Performance Hardware Tuning Storage 144

Percona

MARCH 28, 2023

It’s to ensure that our data is durable after each write operation and to make it persistent and consistent without compromising the performance. In terms of MongoDB, it achieves WAL and data durability using a combination of both Journaling and Checkpoints. Starting with the basics, why is WAL needed in the first place?

Hardware 111

Hardware C++ Storage Cache 111

The Morning Paper

MAY 23, 2019

Compress objects, not cache lines: an object-based compressed memory hierarchy Tsai & Sanchez, ASPLOS’19. Existing cache and main memory compression techniques compress data in small fixed-size blocks, typically cache lines. Hotpads is a hardware-managed hierarchy of scratchpad-like memories called pads.

Cache 61

Cache Benchmarking Hardware Java 61

Scalegrid

APRIL 16, 2020

Since our BYOC plans are hosted through your own AWS or Azure account, all cloud instances, backups and data transfer costs are paid directly through your cloud provider. While this is a good way to get a rough estimate, your monthly cloud costs will indeed vary based on the amount of backups performed and your data transfer activity.

Cloud 242

Cloud Azure AWS Database 242

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. All these contribute significantly towards ensuring smooth functioning.

Metrics 130

Metrics Monitoring Latency Cache 130

ScaleOut Software

APRIL 22, 2020

In this time of extremely high online usage, web sites and services have quickly become overloaded, clogged trying to manage high volumes of fast-changing data. Maintaining rapidly changing data in back-end databases creates bottlenecks that impact responsiveness. The Solution: Distributed Caching.

Cache 52

Cache Storage Servers Database 52

ScaleOut Software

APRIL 22, 2020

In this time of extremely high online usage, web sites and services have quickly become overloaded, clogged trying to manage high volumes of fast-changing data. Maintaining rapidly changing data in back-end databases creates bottlenecks that impact responsiveness. The Solution: Distributed Caching.

Cache 52

Cache Storage Servers Database 52

The Morning Paper

MARCH 8, 2020

This paper describes the design decisions behind the Snowflake cloud-based data warehouse. This paper presents Snowflake design and implementation along with a discussion on how recent changes in cloud infrastructure (emerging hardware, fine-grained billing, etc.) From shared-nothing to disaggregation. joins) during query processing.

Storage 112

Storage Engineering Cache Serverless 112

All Things Distributed

JULY 14, 2015

Streams provide you with the underlying infrastructure to create new applications, such as continuously updated free-text search indexes, caches, or other creative extensions requiring up-to-date table changes. DynamoDB Streams enables your application to get real-time notifications of your tables’ item-level changes. DynamoDB Streams.

Database 158

Database Lambda AWS IoT 158

Brendan Gregg

MARCH 16, 2024

It fails because of a compiler optimization where the frame pointer register is used to store data instead of the frame pointer, but it's just a number so the profiler is unaware this happened and tries to match that address to a function symbol and fails (it is therefore an unknown symbol). You usually get an extra junk frame.

Java 137

Java Cache Google Hardware 137

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

Percona

JUNE 22, 2023

Database uptime and availability Monitoring database uptime and availability is crucial as it directly impacts the availability of critical data and the performance of applications or websites that rely on the MySQL database. Disk space usage Monitor the disk space usage of MySQL data files, log files, and temporary files.

Performance 136

Performance Monitoring Traffic Database 136

Scalegrid

JANUARY 21, 2025

In todays data-driven world, the ability to effectively monitor and manage data is of paramount importance. Redis, a powerful in-memory data store, is no exception. To monitor Redis instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130

Strategy Monitoring Latency DevOps 130

Highly Scalable

APRIL 2, 2012

In particular, we built this system on top of Oracle Coherence and designed our own data structures and indexes. 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.

Ecommerce 100

Ecommerce Cache Storage Architecture 100

Percona

JUNE 22, 2023

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. Fault tolerance aims for zero downtime and data loss. Data replication : Data is continually copied from one database to another to ensure that the system remains operational even if one database fails.

Availability 132

Availability Database Open Source Hardware 132

Percona

MAY 2, 2023

Questions Q: I have a MySQL server with 500 GB of RAM; my data set is 100 GB. ChatGPT: The InnoDB buffer pool is used by MySQL to cache frequently accessed data in memory. Since my data set is 100GB, I would like to see ChatGPT explicitly mention that a good starting point would be 100GB. What could it be?

Social Media 145

Social Media Database Servers Cache 145

Percona

JANUARY 3, 2024

sec) Conclusion These methods provide solutions for ProxySQL backups and restores, which play a pivotal role in safeguarding the integrity of your data and providing defense against various disasters, hardware malfunctions, data loss, and corruption. sec) ProxySQLAdmin> select * from mysql_servers; Empty set (0.00

Traffic 120

Traffic Hardware Cache Servers 120

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Scalegrid

JUNE 14, 2024

In today’s data-driven world, organizations rely heavily on data analysis and visualization to make informed decisions and gain a competitive edge. It provides a user-friendly interface and a wide range of tools to transform raw data into meaningful insights. Why connect Power BI to a MySQL Database?

Database 130

Database Azure Efficiency Servers 130

Percona

AUGUST 8, 2023

As businesses grow and develop, the requirements that they have for their data platform grow along with it. Hardware considerations The first thing we have to consider here is the resources that the underlying host provides to the database. Let’s take a look at each common resource. MySQL has two main memory consumers.

Traffic 98

Traffic Cache Monitoring Database 98

Scalegrid

DECEMBER 21, 2023

In today’s data-driven world, the ability to effectively monitor and manage data is of paramount importance. Redis®, a powerful in-memory data store, is no exception. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130

Strategy Monitoring Latency DevOps 130

Testsigma

JUNE 3, 2021

Otherwise, it may result in the processing of garbage data and erroneous results. Hardware error. We focus on software so much that we forget about the hardware failures. If the hardware gets disconnected or stops working then we cannot expect correct output from the software. Data handling errors. Hardware issues.

Software 82

Software Software Testing Hardware 82

Alex Russell

APRIL 29, 2021

This post mines publicly available data on the pace of compatibility fixes and feature additions to assess the claim. This data set is derived by walking a subset of web platform features exposed to JavaScript and, as such, may not capture the full richness of a particular browser. Reduces data use and improves page load performance.

Media 145

Media Games Education Engineering 145

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. ATC ’19 was refreshingly different. Heterogeneous ISA.

Architecture 12

Architecture Hardware Cache Storage 12

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

JANUARY 18, 2012

s web-based applications often encounter database scaling challenges when faced with growth in users, traffic, and data. Their tables can also grow without limits as their users store increasing amounts of data. Each service encapsulates its own data and presents a hardened API for others to use. History of NoSQL at Amazon â??

Scalability 162

Scalability Database Ecommerce Latency 162

All Things Distributed

SEPTEMBER 20, 2013

Traditionally records in a database were stored as such: the data in a row was stored together for easy and fast retrieval. Combined with the rise of data warehouse workloads, where there is often significant redundancy in the values stored in columns, and database models based on column oriented storage took off.

Storage 72

Storage Hardware Cache C++ 72

The Morning Paper

NOVEMBER 5, 2019

Breaking that assumption allowed Ceph to introduce a new storage backend called BlueStore with much better performance and predictability, and the ability to support the changing storage hardware landscape. But let’s take a quick look at the changing hardware landscape before we go on… The changing hardware landscape.

Storage 64

Storage Systems Hardware Efficiency 64

The Morning Paper

OCTOBER 4, 2020

As is expected to be common during the roll-out and transition phase of 5G, this network adopts the NSA (Non-Standalone Access) deployment model whereby the 5G radio is used for the data plane, but the control plane relies on existing 4G. Application performance. This is because most of the time goes into rendering, i.e., is compute-bound.

Energy 130

Energy Latency Performance Network 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

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

John McCalpin

APRIL 25, 2023

For most high-end processors these values have remained in the range of 75% to 85% of the peak DRAM bandwidth of the system over the past 15-20 years — an amazing accomplishment given the increase in core count (with its associated cache coherence issues), number of DRAM channels, and ever-increasing pipelining of the DRAMs themselves.

Benchmarking 97

Benchmarking Cache Latency Tuning 97