All Things Distributed

AUGUST 22, 2011

Today AWS has launched Amazon ElastiCache , a new service that makes it easy to add distributed in-memory caching to any application. Amazon ElastiCache handles the complexity of creating, scaling and managing an in-memory cache to free up brainpower for more differentiating activities. Driving down the cost of Big-Data analytics.

Cloud 117

Cloud Cache AWS Storage 117

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130

Cache Storage Scalability Architecture 130

All Things Distributed

JUNE 20, 2017

Beyond running their web properties and applications, Next Digital also uses Amazon RDS (database), Amazon ElastiCache (caching), and Amazon Redshift (data warehousing). Next Digital operates on AWS in a more highly available and fault-tolerant environment than their previous colocation solution.

AWS 146

AWS Logistics Cloud Social Media 146

All Things Distributed

DECEMBER 5, 2010

There are two main types of DNS servers: authoritative servers and caching resolvers. But the real robustness of the DNS system comes through the way lookups are handled, which is what caching resolvers do. Caching techniques ensure that the DNS system doesnt get overloaded with queries. No Server Required - Jekyll & Amazon S3.

Cloud 117

Cloud Internet Internet AWS 117

The Netflix TechBlog

OCTOBER 15, 2019

Part I: Overview Andreas Andreakis , Falguni Jhaveri , Ioannis Papapanagiotou , Mark Cho , Poorna Reddy , Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), caching (Memcached etc.),

Transportation 192

Transportation Architecture Processing Storage 192

Scalegrid

FEBRUARY 8, 2024

Handling a storage system spread across multiple physical servers introduces complexities such as unpredictability in behavior, difficulties with testing procedures, and an overall increase in administrative complexity due to the dispersed nature of data.

Storage 130

Storage Systems Big Data Azure 130

ScaleOut Software

NOVEMBER 24, 2020

It sends messages over the cell network to the telematics system, which uses its compute servers (that is, web and application servers) to store incoming messages as snapshots in an in-memory data grid , also known as a distributed cache. The results of batch analysis are typically produced after an hour’s delay or more.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 179

Big Data Cache Engineering Data Engineering 179

All Things Distributed

AUGUST 17, 2011

My templates and blog posts are now located in DropBox and thus locally cached at each machine I use. Driving down the cost of Big-Data analytics. There are a number of pages in the "categories" section that have not been regenerated as according to the website statistics not many of those were accessed.

Servers 126

Servers Social Media AWS Website 126

Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

The Morning Paper

OCTOBER 26, 2020

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104

Cloud Big Data Latency Architecture 104

The Morning Paper

JUNE 23, 2019

Generally to cache data (including non-persistent data that never sees a backing store), to share non-persistent data across application services (e.g. If you want to store time-expiring data that should be shared across application processes, used Memcached or Redis. Fetching too much data in a single query (i.e.,

Cache 79

Cache Latency Google Lambda 79

Smashing Magazine

JULY 29, 2019

MB , that suggests I’ve got around 29 pages in my budget, although probably a few more than that if I’m able to stay on the same sites and leverage browser caching. There’s a trade-off to be made here, as external stylesheets can be cached but inline ones cannot (unless you get clever with JavaScript ). Let’s talk about caching.

Cache 96

Cache Google Mobile Network 96

Abhishek Tiwari

DECEMBER 27, 2017

In 2018, we will see new data integration patterns those rely either on a shared high-performance distributed storage interface ( Alluxio ) or a common data format ( Apache Arrow ) sitting between compute and storage. For instance, Alluxio, originally known as Tachyon, can potentially use Arrow as its in-memory data structure.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Morning Paper

SEPTEMBER 19, 2019

Hyper Dimension Shuffle describes how Microsoft improved the cost of data shuffling, one of the most costly operations, in their petabyte-scale internal big data analytics platform, SCOPE. BlockchainDB – it’s a blockchain underneath, and a database on top.

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

APRIL 27, 2011

We use high-performance transactions systems, complex rendering and object caching, workflow and queuing systems, business intelligence and data analytics, machine learning and pattern recognition, neural networks and probabilistic decision making, and a wide variety of other techniques. Driving down the cost of Big-Data analytics.

Technology 151

Technology Technology AWS Storage 151

ACM Sigarch

NOVEMBER 1, 2019

Alongside more traditional sessions such as Real-World Deployed Systems and Big Data Programming Frameworks, there were many papers focusing on emerging hardware architectures, including embedded multi-accelerator SoCs, in-network and in-storage computing, FPGAs, GPUs, and low-power devices. ATC ’19 was refreshingly different.

Architecture 12

Architecture Hardware Cache Storage 12