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February 03 – 05 , 2016

PgConf.Russia 2016

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Talks

Talks archive

PgConf.Russia 2016
  • Peter Gribanov
    Peter Gribanov 1C LLC

    More than 300.000 developers use technology platform "1C:Enterprise" as a main development tool. I'll tell you about architecture and features that made "1C:Enterprise" one of the most popular development environment in Russia and CIS and about growing popularity of PostgreSQL amongst 1C users.

  • Dmitry Dolgov
    Dmitry Dolgov Zalando SE

    Schema-less is definitely a trend in the data storage nowadays, and it's not only about NoSQL, but also about traditional RDBMS. Many relational databases (e.g. PostgreSQL, Oracle, db2, Mysql) allow to storing data in the schema-less json format and use their own more or less unique way to do that.

    This talk contains two parts:

    • Comparison of the json support in PostgreSQL and different relational databases, namely Mysql, Oracle, db2, MSSql in terms of supported features, functions and so on.
    • Performance benchmarks for databases with the advanced json support, namely PostgreSQL and Mysql, and the MongoDB on different workload types and configurations.

  • Anastasia Lubennikova
    Anastasia Lubennikova PostgresPro

    B-tree is the most widely used index type in PostgreSQL. This data structure and concerned algorithms are developed about forty years ago. But there is still an area for optimisations. In this presentation I'm going to talk about B-tree data structure, and its features important for the optimal index usage. Furthermore, I'll present a couple of new features which are expected to be included in PostgreSQL 9.6 release.

  • Marco Slot
    Marco Slot Citus Data

    CitusDB is an extension for PostgreSQL that can distribute tables across a cluster of PostgreSQL servers. Data is stored in shards that can use append-partitioning for bulk-loading of time series data or hash-partitioning for real-time data ingestion. SELECT queries on distributed tables are transparently parallelised across the cluster, using all available cores. Distributed tables can also be joined in parallel, even if they are not partitioned along the same column. CitusDB is especially suitable for real-time analytics use-cases such as dashboards which require fast analytical queries over live data, and can simultaneously act as a scalable operational database. This talk will describe the internals of CitusDB and give a live demo of a large-scale CitusDB cluster.

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