サクサク読めて、アプリ限定の機能も多数!
トップへ戻る
ノーベル賞
www.datanami.com
OpenTelemetry Is Too Complicated, VictoriaMetrics Says To say the folks at VictoriaMetrics aren’t big fans of OpenTelemetry after implementing its metrics library would be putting it mildly. “OpenTelemetery is so complicated and bloated,” said Aliaksandr Valialkin, the CTO and co-founder of the observability software company. OpenTelemetry is a Cloud Native Computing Foundation (CNCF) project that
The Hadoop dream of unifying data and compute in a distributed manner has all but failed in a smoking heap of cost and complexity, according to technology experts and executives who spoke to Datanami. “I can’t find a happy Hadoop customer. It’s sort of as simple as that,” says Bob Muglia, CEO of Snowflake Computing, which develops and runs a cloud-based relational data warehouse offering. “It’s ve
Hadoop 3 Poised to Boost Storage Capacity, Resilience with Erasure Coding The next major version of Apache Hadoop could effectively double storage capacity while increasing data resiliency by 50 percent through the addition of erasure coding, according to a presentation at the Apache Big Data conference last week. Apache Hadoop version 3 is currently being developed by members of the Apache Hadoop
Google Cloud Dataflow crunched data two to five times faster than Apache Spark in a benchmark test of batch analytics performed by Mammoth Data. While Dataflow’s raw power is impressive, don’t throw in the towel on Spark just yet. If you’re looking to choose a framework to analyze your big data, good luck. With so many options out there, you’ve got your work cut out for you. This embarrassment of
How Uber Uses Spark and Hadoop to Optimize Customer Experience If you’ve ever used Uber, you’re aware of how ridiculously simple the process is. You press a button, a car shows up, you go for a ride, and you press another button to pay the driver. But there’s a lot more going on behind the scene, and much of that infrastructure increasingly runs on Hadoop and Spark, as the Uber data team recently
Marc Andreessen famously said in 2011 that software was eating the world. Four years later, that trend has accelerated, only now it appears that machine learning technology is on the cusp of eating software, and that algorithms will take over the world, with a little help from their friends: the APIs. Not that this is a bad thing, at least not as Elon Musk envisions, with AI-powered overlords ensl
Inside Sibyl, Google’s Massively Parallel Machine Learning Platform If you’ve ever wondered how your spam gets identified in Gmail or where personal video recommendations come from on YouTube, the answer is likely Sibyl, a massively parallel machine learning system that Google developed to make predictions and recommendations with user-specific data culled from its Internet applications. Dr. Tusha
YARN was the big news this week, with the announcement that the Hadoop resource manager is finally hitting the streets as part of the Hortonworks Data Platform (HDP) “Community Preview.” According to Bruno Fernandez-Ruiz, who spoke at Hadoop Summit this week, Yahoo! has been able to leverage YARN to transform the processing in their Hadoop cluster from simple, stodgy MapReduce, to a nimble micro-b
このページを最初にブックマークしてみませんか?
『Datanami: Big Data, Big Analytics, Big Insights』の新着エントリーを見る
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く