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. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility. Pipelining.

Big Data 154

Big Data Processing Lambda Database 154

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., An equally large fraction are due to compute contention, followed by network, cache, memory, and disk contention. ASPLOS’19. Distributed tracing and instrumentation.

Big Data 45

Big Data Cloud Performance Hardware 45

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. Jason Lowe-Power (UC Davis) discussed smart memory management and the need for an efficient interface for it.

Latency 52

Latency Hardware Cache Architecture 52

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130

Cache Storage Scalability Architecture 130

Scalegrid

FEBRUARY 8, 2024

It utilizes methodologies like DStore, which takes advantage of underused hard drive space by using it for storing vast amounts of collected datasets while enabling efficient recovery processes. These systems enable vast amounts of data to be spread over multiple nodes, allowing for simultaneous access and boosting processing efficiency.

Storage 130

Storage Systems Big Data Azure 130

ScaleOut Software

NOVEMBER 24, 2020

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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? Data warehouses.

Artificial Intelligence 202

Artificial Intelligence Storage Analytics Government 202