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September 25 , 2023

PGConf.SPB 2023

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  • 24 talks
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Talks

Talks archive

PGConf.SPB 2023
  • Anton Doroshkevich
    Anton Doroshkevich InfoSoft

    Backup is still a stumbling block when migrating to PostgreSQL from other DBMSs. Its size directly depends on your experience and knowledge about the types of backups in PostgreSQL. In this talk, I will tell you about different types of backups, their pros and cons, and scenarios for using each type.

  • Юрий Темкин
    Юрий Темкин CyberProtect
    Ivan Belinsky
    Ivan Belinsky CyberProtect

    An important aspect of PostgreSQL database security and reliability is backup practices. The talk will reveal the main techniques and methods used to protect data, prevent loss and successfully recover information in case of human error, failures or emergencies. We will tell how CyberBackup helps to protect PostgreSQL, including configuration in Patroni cluster: we will consider system deployment options, important aspects of backup policy configuration, including full and incremental backups. We will also show how to easily work with backups via mount and do granular restores.

  • Aleksandr Kalendaryov
    Aleksandr Kalendaryov DdataGile

    In modern data analysis, machine learning models are used as often as databases. Such IT giants as Google and Amazon have already combined them. Microsoft and Yandex are not far behind. Isn't it time to implement a machine learning model in PostgreSQL? In the report you will hear about the basics of machine learning, its implementation in databases and an example of realization as postres extension.

  • Alexandr Burtsev
    Alexandr Burtsev Postgres Professional
    Sof'ya Kopikova
    Sof'ya Kopikova PostgresPro
    Darya Lepikhova
    Darya Lepikhova PostgresPro

    We will answer the questions about the importance of compression in backup process. Will show a demo how to use the following available algorithms: pglz, zlib, zstd, lz4 in different editions of pg_probackup. We'll show you how to make incremental backups and restore even faster with PTRACK and CFS (tablespace compression) in Postgres Pro. The plans for further development will also be announced.

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