Percona Live 2017 Open Source Database Conference

April 24 - 27, 2017

Santa Clara, California

Time Series Sessions

Featured Time Series Speakers


The Percona Live Open Source Database Conference 2017 has an excellent set of breakout sessions on time series data in our Time Series Data track. These cover InfluxDB, Prometheus, PromQL, Graphite and much more.

Check out how time series applications are used with IoT, cloud, big data and other important enterprise interests.

Below are the talks covering time series data at this year’s conference.

  • 2:20pm to 3:10pm
    Ballroom H
    • Developer
    Mathias Herberts
    Warp 10 is an Open Source solution for managing and analyzing time series data in multiple environments. Warp 10 offers an ingestion and storage layer based on LevelDB or HBase, and a data manipulation environment built around a custom language called WarpScript designed from the ground up for time series data analysis. WarpScript can be leveraged on data residing in Warp 10 or any other oth
    Tools and Techniques Time Series Metrics
  • 4:50pm to 5:15pm
    Room 204
    • Operations
    • Developer
    Brian Hawkins
    Time series data is everywhere and there is a lot of it. This session goes over coding and configuration challenges faced in order to setup the smallest KairosDB/Cassandra cluster that can handle 1 million metrics per second. Topics include: - An introduction to KairosDB - Coding challenges and what didn't work - Configuring Cassandra
    Optimization Time Series Programming

5:15pm to 5:40pm

  • 5:15pm to 5:40pm
    Ballroom E
    • Business / Case Studies
    • Developer
    Baron Schwartz
    In this talk you'll learn how we store and analyze time series data efficiently at VividCortex, using MySQL and Redis as a storage engine. VividCortex's time series workload presents interesting and unusual challenges that most conventional time series databases don't handle well, at a speed and volume that is also unusual.
    MySQL Time Series Metrics
  • 5:15pm to 5:40pm
    Room 204
    • Operations
    • Developer
    Jesse White
    Today's datasets are growing at an exponential rate. Collection, storage, analysis, and reporting are becoming more challenging, and the results more valued. A decade ago, RRDTool's algorithms were well suited to our requirements, but they fall short of scaling to current demands.
    Time Series NoSQL Metrics
  • 11:10am to 12:00pm
    Room 204
    • Developer
    Zburivsky Danil, Christos Soulios
    Data comes in different shapes. One of the these shapes is time series data. Time series is a very important abstraction since it can be used to describe multiple different processes. You can discover patterns in your website users behavior, capture sensor metrics from industrial equipment or track movement of celestial bodies using time series.
    Other OSDB Time Series NoSQL
  • 1:00pm to 1:50pm
    Room 204
    • Developer
    Chris Larsen
    This talk will cover the special case of time series data and the evolution of various schemas from RRD files to RDBMS schemas to NoSQL stores. Particularly we'll focus on why, as the amount of time series data grows and slicing the data by various dimensions becomes important, many users eschewed RDBMS for NoSQL or custom data layers.
    Other OSDB Time Series Metrics
  • 2:00pm to 2:50pm
    Room 204
    • Business / Case Studies
    Michael J. Freedman
    Today everything is instrumented, generating more and more time-series data streams that need to be monitored and analyzed. When it comes to storing this data, many developers often start with some well-trusted system like PostgreSQL, but when their data hits a certain scale, give up its query power and ecosystem by migrating to some NoSQL or other "modern" time-series architecture.
    Time Series
  • 3:30pm to 4:20pm
    Room 204
    • Developer
    Paul Dix
    Over the last year and a half we built an open source storage engine from scratch specifically for time series data. In this presentation I take a deep dive into the storage engine inside InfluxDB. More than just a single storage engine, InfluxDB is two engines in one: the first for time series data and the second, an index for metadata.
    Other OSDB Time Series Programming
  • 4:30pm to 4:55pm
    Ballroom B
    • Developer
    Dmitry Andreev
    ClickHouse is more than just a great «House» for analytics. It can also be used as data storage for Graphite. So, I will explain to you why we decided to try ClickHouse as time-series storage for Graphite despite other existing options (Whisper, Ceres, etc.) And we loved it. Still ClickHouse couldn’t provide for all needs of Graphite (for example, metric search).
    Other OSDB Optimization Time Series

1:50pm to 2:40pm

  • 1:50pm to 2:40pm
    Ballroom G
    • Developer
    Stefan Negrea
    Hawkular Metrics is a scalable, long-term, high performance storage engine for metric data. This session is an overview of the project that includes: history of the project, an overview of the Hawkular ecosystem, technical details of the project, developer features & APIs, and third party integrations.
    Tools and Techniques Time Series Metrics
  • 1:50pm to 2:40pm
    Room 203
    • Operations
    • Developer
    Björn Rabenstein
    Prometheus is an open-source monitoring and alerting system that has quickly gained popularity over the last two years (which includes sophisticated monitoring of MySQL database servers). One of the components of Prometheus is a time-series database (TSDB) embedded into the monitoring server. The TSDB uses a highly domain-specific query language called PromQL.
    Other OSDB Time Series Metrics
  • 3:00pm to 3:50pm
    Room 203
    • Operations
    • Developer
    Justin Teller
    In December 2016, the health and performance monitoring team at Facebook open sourced our in-memory time series database: Beringei. Beringei is different from other in-memory systems, such as memcache, because it has been heavily optimized for storing time series data used specifically for health and performance monitoring.
    Time Series Metrics