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February 05 – 07 , 2018

PGConf.Russia 2018

PGConf.Russia is a leading Russian PostgreSQL international conference, annually taking together more than 500 PostgreSQL professionals from Russia and other countries — core and software developers, DBAs and IT-managers. The 3-day program includes training workshops presented by leading PostgreSQL experts, more than 40 talks, panel discussions and a lightning talk session.

Thems

  • PostgreSQL at the cutting edge of technology: big data, internet of things, blockchain
  • New features in PostgreSQL and around: PostgreSQL ecosystem development
  • PostgreSQL in business software applications: system architecture, migration issues and operating experience
  • Integration of PostgreSQL to 1C, GIS and other software application systems.
  • more than
    0 participants
  • 0 speakers
  • 0
    minutes of conversation
  • 54 talks
  • offline
    format

Talks

Talks archive

PGConf.Russia 2018
  • Игорь Успенский
    Игорь Успенский Rambler&Co

    Rambler & Co is a lot of publications, services and projects. Appear new and grow existing. This environment requires a reliable, fault-tolerant, scalable, automated system.

    I'll tell you about the structure of our PostgreSQL SaaS, what tools and technologies we use. Quorum of 3 Data Centers. A single entry point for clients based on dynamic routing. Emergency switching of the primary server. Transparent scaling for reading. Create a replica without load on the cluster. Transparent transfer of PostgreSQL cluster to other servers. Update dev environment from prod for development. Backup with compression and the use of multiple CPUs on the side of the database, the restoration of one database from basebackup. Monitoring of sql queries.

  • Alexander Korotkov
    Alexander Korotkov PostgresPro

    Bringing the provability and immutability of blockchain to performance and efficiency of traditional DBMS.

    Blockchain technology has several unique properties including provability and immutability. Every blockchain transaction is signed by its author, and it could be verified by any blockchain network member. Also, once data is stored in blockchain, it can't be altered in the future. Many databases operating traditional DBMS would also benefit from provability and immutability properties. However, inclusion of all the transaction data in the public blockchain is very expensive.

    Credereum is the platform, which allows creation and maintaining of databases, whose contents and history are provable and immutable without sacrifice the performance and efficiency of traditional DBMS. Thanks to Credereum, database owner can prove the validity of query results, while users can verify them. Database owner don't have to reveal the whole database contents or full history of transactions to provide the proof of database query results. Therefore, Credereum database may contain private sensitive information. Credereum utilized bleeding-edge technologies including, but not limited to decentralized cloud, public blockchain with sharding. Credereum is an emerging technology of trusted and private databases.

    We will explain why PostgreSQL is suitable database for Credereum and what we need to develop in Postgres to support signed transactions and cryptographic storage.

  • Ivan Frolkov
    Ivan Frolkov PostgresPro

    Apart from its main purpose of scheduling tasks, pgpro_scheduler can also deal with chained transactions. It can be used in various scenarios of asynchronous data processing.

    This tutorial demonstrates pgpro_scheduler features that ensure secure processing of chained transactions. We'll be using cryptocurrency transactions as an example.

    pgpro_scheduler is included into Postgres Pro Enterprise as an extension.

  • Darafei Praliaskouski
    Darafei Praliaskouski Juno

    PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

    Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.

All talks

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