Managing moving objects data with MobilityDB

MobilityDB is a moving object database extension to PostgreSQL and PostGIS. It has types and functions for storing an querying geospatial trajectories, as first class citizens. The main type is called tgeompoint (temporal geometry point). It represents a complete movement track of a geometry point, such as a car, a bird, or a person. The function speed(tgeompoint) computes the time varying speed of the object, as a tfloat (temporal float). Similar to these examples, MobilityDB has 6 temporal types, and over 300 functions. As such, it is a function-rich platform for Mobility Data Management.

In this tutorial you will:

• learn about moving object databases
• write MobilityDB SQL queries and explore a database of geospatial trajectories
• walk through the different type, indexes, and functions of MobilityDB.

Deploying PostgreSQL Cluster with Query Load Balancing and Monitoring Capabilities on Kubernetes

Kubernetes is an open source container orchestration platform for automating deployment, scaling and management of application containers. Nowadays, more and more applications are being deployed in containers on Kubernetes.

There are several solutions that can help us to run a PostgreSQL cluster on Kubernetes. However, these solutions don't provide query load balancing capability. In this talk, I will show you how to combine PostgreSQL Operator with Pgpool-II to deploy a PostgreSQL cluster with query load balancing capability on Kubernetes.

Monitoring is a very important part in production environments. Although Kubernetes provides a basic way to monitor the status of a PostgreSQL cluster, this is not sufficient for managing a PostgreSQL cluster in production. An important improvement of Pgpool-II 4.2 release is the ability to output more useful statistics of the PostgreSQL cluster. In this talk, I will describe how to monitor and visualize the PostgreSQL cluster statistics in Prometheus for extensive cluster monitoring.

High-Performance PostgreSQL

PostgreSQL is one of the leading open-source databases. Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. The default configuration is designed in such a way that PostgreSQL can run on any system using minimum resources. Consequently, a default installation of PostgreSQL does not give optimum performance on the high-performance machine because it is set up to use all available resources. PostgreSQL provides mechanisms that allow you to tune your database according to your workload and machine specification. Outside of PostgreSQL, though, we can tune the Linux kernel to allow the database load to work optimally. In this talk, we will learn how to tune some of the PostgreSQL’s parameters, and we will see the effect of that tuning, but we will focus on demonstrating how to tune Linux for better Postgres performance. As there are so many Linux kernel parameters that can be tuned to improve the performance of PostgreSQL, I will also share the results of benchmarks obtained when tuning some of the Linux parameters.

Backup Best Practices with pgBackRest

Backups are a critical part of any enterprise database solution but they are often done poorly or skipped altogether, which can lead to data loss in the event of hardware failure or some other disaster.

In this talk we'll cover database backup best practices and how to implement them with pgBackRest, including:

• WAL archiving and retention
• Backup frequency and retention
• How to meet recovery time/point objectives
• Configuration options
• Performance considerations