Hive

product on 3 shows · 4 statements across 4 episodes · said 1 times in 1 episodes since 2021

We Live to Build 1 the MAD Podcast the a16z Podcast

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We Live to Build 1

2021 1 mention in 1 episode

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4 statements about Hive, every show

MAD Assertion Not checkable as stated
Dasdan's past teams built custom Kafka alternatives to handle 100 petabytes
“In the past, when we were doing data platform, there was no Kafka, for example, we created a Kafka-like system ourselves, but we are lucky that, yeah, we created an HBase, sort of HHive-like system ourselves with hundred petabytes of size of data, right?”
Ali Dasdan Sep 19, 2024 ▶ 22:36 AI at ZoomInfo: Superpowering GTM teams | Ali Dasdan, CTO, ZoomInfo
a16z Assertion Supported
Legacy Hadoop tools like Hive, Pig, and Mahout now run on Spark
“So in particular you know, one of the things we saw is many of the projects that were built on top of Hadoop, such as Hive, which is a SQL processing at scale and Pig and Mahout for machine learning are starting to run on top of Spark as well, so that users of…”
Matei Zaharia Jan 2, 2019 ▶ 13:59 a16z Podcast | A Conversation With the Inventor of Spark
MAD Assertion Supported
Facebook built Hive to provide a SQL interface on Hadoop
“Facebook built Hive, right, because they needed a tool to sit on top of Hadoop, you know, to allow their business analysts to kind of sequel interface to this big data platform.”
Todd Papaioannou Dec 5, 2013 ▶ 20:08 Panel: Continuuity, Sailthru and Visual Revenue // Data Driven NYC #7 // June 2012
MAD Assertion Not checkable as stated
Mike Driscoll: Installing Hive on a Hadoop cluster increases usage by 10x
“Once you install Hive onto Hadoop cluster, usage of that cluster typically goes up by a factor of 10 because you lower the friction of getting data out of that system.”
Mike Driscoll Dec 5, 2013 ▶ 31:06 Panel: Metamarkets, Kaggle and Quid // Data Driven NYC #4 // Mar 2012

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