Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. As a result, the input data typically goes from the data source to the in-stream pipeline via a persistent buffer that allows clients to move their reading pointers back and forth.

Big Data 154

Big Data Processing Lambda Database 154

All Things Distributed

DECEMBER 8, 2016

Given this, enterprises, public sector bodies, startups, and small businesses are looking to adopt agile, scalable, and secure public cloud solutions. Access to secure, scalable, low-cost AWS infrastructure in Canada allows customers to innovate and provide tools to meet privacy, sovereignty, and compliance requirements. Scalability.

AWS 155

AWS Cloud Lambda Innovation 155

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

The Morning Paper

JUNE 23, 2019

After all, we’ve been doing that forever with the 2nd-level cache of ORMs , and it is highly encouraged in e.g. the AWS Lambda programming model — which was born on the cloud— to help mitigate function start-up times. We’ve seen similar high marshalling overheads in big data systems too.) From RInK to LInK.

Cache 79

Cache Latency Google Lambda 79