VoltDB

DECEMBER 11, 2024

Data interception during transit. Use hardware-based encryption and ensure regular over-the-air updates to maintain device security. Data Overload and Storage Limitations As IoT and especially industrial IoT -based devices proliferate, the volume of data generated at the edge has skyrocketed.

IoT 52

IoT Energy Logistics Latency 52

All Things Distributed

AUGUST 24, 2012

Werner Vogels weblog on building scalable and robust distributed systems. Which makes this week a good moment to read up on some of the historical work around the costs of data engineering. In 1997 Jim revisted his caculations with the help of Goetz Graefe , and it details the impact of 10 years of hardware and pricing progress.

Storage 85

Storage Hardware AWS Data Engineering 85

All Things Distributed

OCTOBER 7, 2015

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. QuickSight is a fast, cloud native, scalable, business intelligence service for the 1/10th the cost of old-guard BI solutions.

Cloud 112

Cloud Big Data AWS Analytics 112

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Latency 63

Latency Analytics Scalability Engineering 63

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Native frameworks.

Big Data 63

Big Data Storage Benchmarking Hardware 63

O'Reilly

JULY 15, 2020

Technical roles represented in the “Other” category include IT managers, data engineers, DevOps practitioners, data scientists, systems engineers, and systems administrators. Combined, technology verticals—software, computers/hardware, and telecommunications—account for about 35% of the audience (Figure 2).

Database 145

Database Architecture Education Systems 145