PostgreSQL & Java Tutorial

Java is one of the most used languages when programming with PostgreSQL databases. Join this tutorial to learn or review the techniques to connect to postgres, best programming practices with JDBC, and to explore jOOQ, a mapper software that allows you to use the full power of SQL and postgres advanced query features while avoiding all the boilerplate code.

This tutorial is very practical: most of the time will be dedicated to iterate through code samples. It will cover:

• Introduction to Java and PostgreSQL
• Ways of connecting to PostgreSQL from Java (not only JDBC!)
• Introduction to JDBC. JDBC types. PostgreSQL JDBC
• Code demo: JDBC with PostgreSQL. From Java 1.4 to Java 8, best practices and code samples
• Code demo: jOOQ, a great mapper for PostgreSQL
• Java inside PostgreSQL
• The future of Java and PostgreSQL

About two-thirds of the tutorial will be dedicated to iterate over code samples and demos. All the code would be available from public open-source repositories and built with maven, so that any attendee may download it and build easily to play with it during the tutorial (although not required).

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Part 1

Part 2

Part 3

Part 4

Building high-performance scale-out Database Solutions

Modern high-performance and scale-out Database solutions need to move huge amounts of data between the system components. They need to perform it quickly and without delay for the end-user. While developing interconnect technologies Mellanox focuses on highest bandwidth, ultra-low latency, and advanced CPU offload capabilities. In this session Michael will tell about fast interconnect value for Database and Big Data solutions and will share Mellanox experience in building such systems in cooperation with leading global vendors.

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Automation of migration to PostgreSQL from various databases

The report is focused on the topic of automation of migration to PostgreSQL from other databases using Ispirer Migration and Modernization Toolkit. The issues of data and SQL code migration, conversion of client applications, embedded SQL and database API will be covered, the examples of implemented projects of migration from Oracle to PostgreSQL and from Microsoft SQL Server to PostgreSQL will be given.

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Towards 1M writes/sec: Scaling PostgreSQL using Citus MX

Citus allows you to distribute postgres tables across many servers. It extends postgres to transparently delegate or parallelise work across a set of worker nodes, enabling you to scale out the CPU and memory available for queries.

One year ago, we began a long journey to allow Citus to scale out another dimension: write throughput. With writes being routed through a single postgres node, write throughput in Citus was ultimately bottlenecked on the CPUs of a single node. Citus MX is a new edition of Citus which allows distributed tables to be used from from any of the nodes, enabling NoSQL-like write-scalability.