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March 15 – 17 , 2017

Postrelease

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Talks

Talks archive

PgConf.Russia 2017
  • Ivan Panchenko
    Ivan Panchenko PostgresPro

    This tutorial is about various applied JSON usage patterns and the related PostgreSQL functionality. We will discuss data storage in the JSON format, retrieving, changing, and searching such data, JSON features for simple SQL queries, as well as using JSON in stored procedures in different languages. You’ll get hands-on experience with some of the discussed problems on the provided virtual machines.

  • Ivan Panchenko
    Ivan Panchenko PostgresPro

    A summary of what the Postgres Professional company has achieved in its two-year history:

    • Our achievements in PostgreSQL development.
    • What is the Russian Postgres Pro DBMS, and how is it related to PostgreSQL?
    • What is Postgres Pro Enterprise, and why Enterprise?
    • What about trainings and certification?

    VIDEO

  • Dmitry  Lebedev
    Dmitry Lebedev BestPlace

    Nowadays one can make a decent urban research based simply on public datasets, making interesting and unexpected insights. In the presentation, I'll show examples of these calculations in PostGIS, the industry standard de-facto.

    But just PostGIS is not enough. You need tools to import, verify and visualize the data. It's critically important to visualize the data live, to debug your calculations and shorten iterations. I'll describe all these steps:

    1. Collecting the data: public API, OpenStreetMap; direct user input.
    2. 3rd party APIs for calculations.
    3. Visualization of GIS and other sorts of data: QGIS, Matplotlib, Zeppelin integrated with PostGIS.
    4. Debugging the calculations: live visualization (Arc, QGIS, NextGIS Web)
    5. Scripting and minimizing the chores: Makefile, Gulp

  • Marco Slot
    Marco Slot Citus Data

    Citus allows you to distribute postgres tables across many servers. It extends postgres to transparently delegate or parallelise work across a set of worker nodes, enabling you to scale out the CPU and memory available for queries.

    One year ago, we began a long journey to allow Citus to scale out another dimension: write throughput. With writes being routed through a single postgres node, write throughput in Citus was ultimately bottlenecked on the CPUs of a single node. Citus MX is a new edition of Citus which allows distributed tables to be used from from any of the nodes, enabling NoSQL-like write-scalability.

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