The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

MARCH 2, 2011

Japanese companies and consumers have become used to low latency and high-speed networking available between their businesses, residences, and mobile devices. The advanced Asia Pacific network infrastructure also makes the AWS Tokyo Region a viable low-latency option for customers from South Korea. At werner.ly Syndication.

AWS 112

AWS Cloud Games Latency 112

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 211

Artificial Intelligence Analytics Storage Government 211

All Things Distributed

DECEMBER 14, 2011

This new Region has been highly requested by companies worldwide, and it provides low-latency access to AWS services for those who target customers in South America. The new Sao Paulo Region provides better latency to South America, which enables AWS customers to deliver higher performance services to their South American end-users.

AWS 114

AWS Latency Storage Big Data 114

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Scalability Architecture 130

All Things Distributed

AUGUST 16, 2011

There are different considerations when deciding where to allocate resources with latency and cost being the two obvious ones, but compliance sometimes plays an important role as well. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics.

AWS 111

AWS Government Big Data Cloud 111

All Things Distributed

JULY 13, 2010

Further computationally intensive, highly parallel workloads have found their way to Amazon EC2 as businesses have explored using HPC types of algorithms for other application categories, for example to to process very large unstructured data sets for Business Intelligence applications. Driving Storage Costs Down for AWS Customers.

Cloud 118

Cloud AWS Automotive Latency 118

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. At werner.ly

AWS 85

AWS Storage Cloud Big Data 85

All Things Distributed

DECEMBER 3, 2009

This new Region consists of multiple Availability Zones and provides low-latency access to the AWS services from for example the Bay Area. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. blog comments powered by Disqus.

AWS 60

AWS Cloud Latency Storage 60

All Things Distributed

APRIL 28, 2010

Customers can now store their data and run their applications from our Singapore location in the same way they do from our other U.S. There are four main reasons to do so: Performance - For many applications and services, data access latency to end users is important. Driving Storage Costs Down for AWS Customers.

AWS 61

AWS Cloud Latency Storage 61

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

All Things Distributed

DECEMBER 5, 2010

Low-latency query resolution The query resolution functionality of Route 53 is based on anycast, which will route the request automatically to the DNS server that is the closest. This achieves very low-latency for queries which is crucial for the overall performance of internet applications. At werner.ly Syndication. or rss feed.

Cloud 117

Cloud Internet Internet AWS 117

All Things Distributed

NOVEMBER 19, 2010

Understanding Throughput-Oriented Architectures - background article in CACM on massively parallel and throughput vs latency oriented architectures. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. At werner.ly Syndication.

AWS 67

AWS Cloud Benchmarking Storage 67

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20. Emphasis mine ).

Cloud 104

Cloud Big Data Latency Architecture 104

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

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

The Morning Paper

JUNE 23, 2019

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. If you want to store time-expiring data that should be shared across application processes, used Memcached or Redis.

Cache 79

Cache Latency Google Lambda 79

All Things Distributed

DECEMBER 12, 2018

They can run applications in Sweden, serve end users across the Nordics with lower latency, and leverage advanced technologies such as containers, serverless computing, and more. The first platform is a real time, big data platform being used for analyzing traffic usage patterns to identify congestion and connectivity issues.

AWS 124

AWS Cloud Games Serverless 124

All Things Distributed

NOVEMBER 15, 2010

For example, the most fundamental abstraction trade-off has always been latency versus throughput. Modern CPUs strongly favor lower latency of operations with clock cycles in the nanoseconds and we have built general purpose software architectures that can exploit these low latencies very well. General Purpose GPU programming.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

FEBRUARY 24, 2010

If you need to achieve high-availability and scalable performance, you will need to resort to data replication techniques. For example updates to data now needs to happen in several locations, so what do you do if one or more of those locations is (temporarily) not accessible? Data Consistency Models in the Amazon Services.

AWS 69

AWS Latency Database Scalability 69

Testsigma

FEBRUARY 12, 2021

When more companies transition into digital-first projects, there must be an expanded number of processes and IT data departments to keep IT teams on track. of companies invest over US$ 50 million in initiatives such as Artificial Intelligence (AI) and Big Data in 2020, up from 39.7% Automation to Enhance AI Security Defence.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92