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. Support diverse analytics workloads. What is a data lakehouse? Reduced redundancy.

Artificial Intelligence 205

Artificial Intelligence Analytics Storage Government 205

Scalegrid

DECEMBER 21, 2023

To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency.

Strategy 130

Strategy Monitoring Latency DevOps 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

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. As a result of these different types of usages, a number of interesting research challenges have emerged in the domain of visual computing and artificial intelligence (AI). interactive AR/VR, gaming and critical decision making).

Wireless 54

Wireless IoT Analytics Architecture 54

Abhishek Tiwari

DECEMBER 27, 2017

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. In contrast, Alluxio a middleware for data access - think Alluxio storage layer as fast cache. Machine learning meets data integration.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49