ACM Sigarch

MAY 31, 2023

Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. However, building and utilizing HCM presents challenges, including interconnecting various memory technologies (e.g.,

Latency 52

Latency Hardware Cache Architecture 52

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

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

JUNE 20, 2017

The new region will give Hong Kong-based businesses, government organizations, non-profits, and global companies with customers in Hong Kong, the ability to leverage AWS technologies from data centers in Hong Kong. The new AWS Asia Pacific (Hong Kong) Region will have three Availability Zones and be ready for customers for use in 2018.

AWS 146

AWS Logistics Cloud Social Media 146

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 209

Artificial Intelligence Storage Analytics Government 209

ScaleOut Software

NOVEMBER 24, 2020

The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. Current Telematics Architecture.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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

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

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

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

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

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

Smashing Magazine

JULY 29, 2019

Many of us are lucky enough to be on mobile plans which allow several gigabytes of data transfer per month. Failing that, we are usually able to connect to home or public WiFi networks that are on fast broadband connections and have effectively unlimited data. The Cost Of Mobile Data. Data is expensive in parts of Europe too.

Cache 96

Cache Google Mobile Network 96

The Morning Paper

SEPTEMBER 19, 2019

Their dataset has about 7B edges… Meanwhile, AnalyticDB is Alibaba’s real-time OLAP RDBMS handling 10PB of data (in excess of 100 trillion rows!). 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.

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

APRIL 27, 2011

To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Given that I have frequently written about many of these technologies on this blog I asked investor relations to be allowed to reprint it here.

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