PgConf.Russia 2020

MobilityDB is an open source moving object database system (https://github.com/ULB-CoDE-WIT/MobilityDB). Its core function is to efficiently store and query mobility tracks, such as vehicle GPS trajectories. It implements the Moving Features specification from the Open Geospatial Consortium (OGC). MobiltyDB is engineered up from PostgreSQL and PostGIS, providing spatiotemporal data management via SQL. It thus integrates with the postgreSQL eco-system allowing for complex architectures such as mobility stream processing and cloud deployments.

The presentation will explain the architecture of MobilityDB, its database types, indexes, and operations. We will highlight the PostgreSQL features that enable this extension, and the would like to have features. This presentation will be of special interest to the PostgreSQL community, and to professionals in the transportation domain.

PostgreSQL 13 Feature Freeze is scheduled for April 2020. Two more commitfests are still accepting new patches. What we can say about PostgreSQL 13. It's possible that rotation rule will work so that new release wouldn't have as many new features as PostgreSQL 12 have. If even it is do, that would be good evolutionary release with a lot of medium feature and infrastructure changes, which prepares postgres for new leap. In this talk I will overview expected novelties in PostgreSQL 13. It would be more or less accurate, since there would be only one commitfest left, which results are possible to forecast.

This talk discusses the open source components we use at Adjust to manage a massive number (5+PB) of application log messages on PostgreSQL in a massively multi-parallel way. It provides both a use case for PostgreSQL in a big data (high volume/velocity/variety) environment, and can be used to show the power of PostgreSQL with JSONB, GIN, and more.

This talk covers the capabilities of the components in depth, sufficient to inspire similar solutions.

Patroni and Stolon are two of the most popular and advanced solutions for orchestrating PostgreSQL and ensuring auto-failover for clusters with the Leader-Followers configuration. However, engineers who migrate from good old tools like Corosync&Pacemaker or built-in solutions of other DBMS often run into issues when installing these tools and figuring out the purpose of each component.
In this tutorial, we will go through a typical installation procedure of Patroni and Stolon clusters on virtual machines (not in containers), as well as review their behavior in case of various infrastructure failures. The whole process will be demonstrated on three vagrant virtual machines with pre-built images. You can follow along on your own system if you set up the required environment.