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.

Developers are often challenged to deliver results that are hard to implement using simple SQL queries. Fortunately, complex SQL capabilities exist in the SQL standards — common table expressions and window functions.

SQL is a declarative language, meaning the user submits an SQL command and the database determines the optimal execution. Common Table Expressions (CTEs) allow queries to be more imperative, allowing looping and processing hierarchical structures that are normally associated only with imperative languages.

Normal SQL queries return rows where each row is independent of the other returned rows. SQL window functions allow queries to return computed columns based on values in other rows in the result set.

This tutorial will help developers use CTE queries in their applications and allow operations that normally could only be done in application code to be done via SQL queries. It also explains the many window function facilities and how they can be used to produce useful SQL query results.

Video

Part I «Programming the SQL Way with CTE»

Part II «Postgres Window Magic»

Lately, the PostgreSQL is more widely being used for Enterprise. Our company, Ingram Micro Cloud, is one of the first companies that did it. We have been using PostgreSQL for many years as the main DBMS for our products. In our report, we want to tell about the evolution of our High Availability (HA) PostgreSQL cluster. We will tell about how quickly we implemented the solution using pgpool-II, wrote failover scripts, tested Postgres-XL, and came up with unusual configurations of Stolon. We will also cover the problems of load balancing, pooling connections, and backups.

Tutorial will show specifics of server programming in these languages. I will present practical examples and compare the features of these languages in PostgreSQL environment from the viewpoint of solving practical tasks.