PGConf.Russia 2018

Bringing the provability and immutability of blockchain to performance and efficiency of traditional DBMS.

Blockchain technology has several unique properties including provability and immutability. Every blockchain transaction is signed by its author, and it could be verified by any blockchain network member. Also, once data is stored in blockchain, it can't be altered in the future. Many databases operating traditional DBMS would also benefit from provability and immutability properties. However, inclusion of all the transaction data in the public blockchain is very expensive.

Credereum is the platform, which allows creation and maintaining of databases, whose contents and history are provable and immutable without sacrifice the performance and efficiency of traditional DBMS. Thanks to Credereum, database owner can prove the validity of query results, while users can verify them. Database owner don't have to reveal the whole database contents or full history of transactions to provide the proof of database query results. Therefore, Credereum database may contain private sensitive information. Credereum utilized bleeding-edge technologies including, but not limited to decentralized cloud, public blockchain with sharding. Credereum is an emerging technology of trusted and private databases.

We will explain why PostgreSQL is suitable database for Credereum and what we need to develop in Postgres to support signed transactions and cryptographic storage.

Azure Database for PostgreSQL is a managed database service built for developers using the community PostgreSQL database technology you love. Learn how you can leverage the managed service and the key capabilities that the service offers which enables you as a developer to focus on developing apps. Using customer stories and experiences including live demos, we will walk through best practices and demonstrate how this service integrates with the other Azure services.

In the last six months I have been working with a massive OLAP environment with 20TB shards, spanning around 400TB of data. Come to listen to how we make it all work, the challenges, and the skills involved. This talk has very little in common with the 10TB and Beyond talk because the data environments are very different.

We will cover analytics performance, data alignment, reasons for building extensions in C, and moving data around between servers in multiple data centers.

WAL-G is simple and effective disaster recovery tool for PostgreSQL using cloud storages. In its core functionality, WAL-G is the successor of WAL-E rewritten in Go. But there is one new neat feature - delate-backups. WAL-G delta-backups, whenever possible, stores only pages, changed since the previous backup. In this talk, I'm going to describe development process of this feature.

Surprisingly, most important and complicated question was the design of the interface: WAL-e is simple and comprehensive, keeping these properties was goal #1. Technical details of implementation were covering some underwater stones too. Besides these, I want to discuss the perspective of technological development and future coordination of recovery tools developers.