Efficiently storing and real-time querying TBs of time series data with Paul Dix


Details
Paul Dix, organizer of the NYC Machine Learning meetup will speak to us about InfluxDB, a distributed time series database.
We should have a number of giveaways, including a book or two.
The Talk:
In this talk I'll introduce InfluxDB (http://influxdb.org/), a distributed time series database we open sourced based on our backend infrastructure at Errplane (https://errplane.com/). I'll talk about why you'd want a database specifically for time series and cover the API and some of the key features of InfluxDB, including:
• Stores metrics (like Graphite) and events (like page views, exceptions, deploys)
• No external dependencies (self contained binary)
• Fast. Handles many thousands of writes per second on a single node
• HTTP API for reading and writing data
• SQL-like query language
• Distributed to scale out to many machines
• Built in aggregate and statistics functions
• Built in downsampling
I'll talk about the underlying technology and some of the tradeoffs we made in the design to help it scale with time series data.
Bio:
Paul Dix (https://twitter.com/pauldix) is co-founder and CEO of the Y-Combinator (http://ycombinator.com/) backed company Errplane (https://errplane.com/). Paul is the series editor for Addison Wesley's "Data & Analytics (http://www.amazon.com/s/ref=nb_sb_noss_1?url=search-alias%3Dstripbooks&field-keywords=Addison-Wesley%20Data%20and%20Analytics%20Series)" series and the author of “Service Oriented Design with Ruby and Rails (http://www.amazon.com/Service-Oriented-Design-Rails-Addison-Wesley-Professional/dp/0321659368/ref=sr_1_1?s=books&ie=UTF8&qid=1383318549&sr=1-1&keywords=paul+dix).” He is a frequent speaker at conferences and user groups including Web 2.0, RubyConf, RailsConf, and GoRuCo. Paul is the founder and organizer of the NYC Machine Learning Meetup (https://www.meetup.com/NYC-Machine-Learning/). In the past he has worked at startups and larger companies like Google, Microsoft, and McAfee. He lives in New York City.
Pizza begins at 6:30 (Knewton asks that people please do not arrive earlier than this), Paul will begin at 7 and then we head to the local bar.

Efficiently storing and real-time querying TBs of time series data with Paul Dix