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. Contact Info. Werner Vogels.

AWS 60

AWS Cloud Latency Storage 60

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

DECEMBER 5, 2010

A simple example is the situation with Persons and Telephones; a person has a name, a person can have one or more telephones and each phone can have one or more telephone numbers. Modern systems require much faster update propagation to for example deal with outages. Driving Storage Costs Down for AWS Customers. No lock-in.

Cloud 117

Cloud Internet Internet AWS 117

All Things Distributed

APRIL 28, 2010

There are four main reasons to do so: Performance - For many applications and services, data access latency to end users is important. The new Singapore Region offers customers in APAC lower-latency access to AWS services. Jurisdictions - Some customers face regulatory requirements regarding where data is stored.

AWS 61

AWS Cloud Latency Storage 61

The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

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

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. A high CPU cost due to marshalling data to/from the RInK store formats to the application data format. Who knew! ;).

Cache 79

Cache Latency Google Lambda 79

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Highly Scalable

MAY 1, 2012

This approach often leads to heavyweight high-latency analytical processes and poor applicability to realtime use cases. The picture above depicts the fact that this data set basically occupies 40MB of memory (10 million of 4-byte elements). what is the cardinality of the data set)?

Analytics 191

Analytics Traffic Big Data Efficiency 191

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. Where to go from here?

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? Lowest read latency. Higher read latency.

AWS 69

AWS Latency Database Scalability 69