Scalegrid

FEBRUARY 8, 2024

Opting for synchronous replication within distributed storage brings about reinforced consistency and integrity of data, but also bears higher expenses than other forms of replicating data. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

NOVEMBER 20, 2023

Whether in analyzing A/B tests, optimizing studio production, training algorithms, investing in content acquisition, detecting security breaches, or optimizing payments, well structured and accurate data is foundational. Backfill: Backfilling datasets is a common operation in big data processing.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. We will cover a few core concepts in the Data Mesh Schema domain. See example below.

Big Data 253

Big Data Government Analytics Processing 253

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

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., on end-to-end latency) and less than 0.15% on throughput. This tracing system is similar to Dapper and Zipkin and records per-microservice latencies and number of outstanding requests. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

The Netflix TechBlog

NOVEMBER 3, 2023

An example of a Data Mesh pipeline which moves and transforms data using Union, GraphQL Enrichment, and Column Rename Processor before writing to an Iceberg table. The existing Data Mesh Processors have a lot of overlap with SQL.

Processing 265

Processing Engineering Infrastructure Latency 265

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. Let’s look at the Azure DB for MariaDB overview as an example. See the health of your big data resources at a glance. Azure Virtual Network Gateways.

Azure 150

Azure Cloud Big Data Virtualization 150

All Things Distributed

NOVEMBER 5, 2015

This region will provide even lower latency and strong data sovereignty to local users. Here are some examples of how our UK customers are using the AWS platform: Hot Startups – Shazam , Hailo , Omnifone , Yplan , SwiftKey , Aire , GoSquared. Public Sector & Not-for-Profit – UCAS , Makewaves , JustGiving.

AWS 167

AWS Retail Entertainment IoT 167

ScaleOut Software

JULY 19, 2021

This architecture does not apply computing resources to track the myriad data sources sending telemetry and continuously look for issues and opportunities that need immediate responses. The complex web of communicating devices that surrounds us needs intelligent, real-time device tracking to extract its full benefits.

IoT 78

IoT Analytics Big Data Architecture 78

The Netflix TechBlog

DECEMBER 21, 2020

For example, we allow a partition to have a few small files instead of always merging files in perfect sizes. These principles reduce resource usage by being more efficient and effective while lowering the end-to-end latency in data processing. Since then, we have moved our ingestion to Keystone and our table layout to Iceberg.

Storage 203

Storage Latency Efficiency Data Engineering 203

All Things Distributed

JANUARY 6, 2016

A region in South Korea has been highly requested by companies around the world who want to take full advantage of Korea’s world-leading Internet connectivity and provide their customers with quick, low-latency access to websites, mobile applications, games, SaaS applications, and more.

AWS 110

AWS Cloud Games Latency 110

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 98

Big Data Mobile Latency Database 98

The Morning Paper

JUNE 23, 2019

A high CPU cost due to marshalling data to/from the RInK store formats to the application data format. In ProtoCache (a component of a widely used Google application), 27% of its latency when using a traditional S+RInK design came from marshalling/un-marshalling. Fetching too much data in a single query (i.e.,

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

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

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

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 down the cost of Big-Data analytics. We have expanded the AWS footprint in the US and starting today a new AWS Region is available for use: US-West (Northern California).

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 down the cost of Big-Data analytics.

Cloud 118

Cloud AWS Automotive Latency 118

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

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 down the cost of Big-Data analytics.

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

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