NORM - No ORM Framework

It's a well-known fact, that although the database performance is great, and each query is executed in milliseconds, the overall application response time may be slow, making the users wait for a response for an extended period of time. We know that the problem is not the database, but the way the application developers communicate with the database. Specifically, we are talking about ORMs - Object-Relational Mappers. Database developers hate them, but application developers love them because they allow developing applications without any knowledge of database internals. As a result, the system performance is often unacceptably slow.

The only way to change this behavior is to provide application developers with a tool, which is as easy to use, as an ORM, but which will allow escaping the common ORM pitfalls. That's why we developed NORM - No-ORM Framework. During this presentation, we will go over examples of code from https://github.com/hettie-d/NORM repo and learn how to build "transport objects" for efficient data transfer between applications and databases

psycopg3: all the love between Python and PostgreSQL

Python is today one of the most used programming languages in the world: simple to learn and to use and ready to interface to any known service and protocol. psycopg2 is the most used PostgreSQL driver for Python: it offers good performance and makes the communication between the language and the database as smooth as possible.

Python has evolved enormously in the past years and its first-class support for async programming is changing the way new programs are written. PostgreSQL has evolved too: a new generation of the driver is needed to make the most of all the features it has to offer.

psycopg3 is the new generation of the most used Python-PostgreSQL adapter: it offers a familiar interface and smooth upgrade path, but behind the scenes it is engineered to obtain the best performance from the database and the language: async programming, prepared statements, binary parameters.

psycopg3 is also experimenting with innovative JSONB support and query pipelining! Come and discover the forefront of the research between your most loved language and database!

SQL as data

Almost every business app is essentially just a SQL generator. How to easily build and compose SQL queries? I will explain the "Clojure way" of representing SQL as data (data DSL) and show how it may help you to dynamically build and compose SQL queries up to macros and query analysis.

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.