PgConf.Russia 2016

Greenplum is a PostgreSQL fork, optimized for Analytics and Data Warehouse use cases. Pivotal announced in early 2015 that a number of products will go Open Source, one of them is Greenplum Database. This talk provides an overview over the history of Greenplum, the entire process of bringing the product into Open Source, all the stumbling blocks we ran into, and explains how contributors can participate.

Schema-less is definitely a trend in the data storage nowadays, and it's not only about NoSQL, but also about traditional RDBMS. Many relational databases (e.g. PostgreSQL, Oracle, db2, Mysql) allow to storing data in the schema-less json format and use their own more or less unique way to do that.

This talk contains two parts:

• Comparison of the json support in PostgreSQL and different relational databases, namely Mysql, Oracle, db2, MSSql in terms of supported features, functions and so on.
• Performance benchmarks for databases with the advanced json support, namely PostgreSQL and Mysql, and the MongoDB on different workload types and configurations.

The Korean PostgreSQL User Group has been relatively small and inactive for many years. However, recently things are changing in Korea. Companies are seeking to alternatives for their expensive proprietary RDBMS in order to cut their TCO. And the government institutes also participate in this trend. We, Bitnine, are leading these changes in Korea. We launched the first version of our PostgreSQL solution, Agens SQL in 2015. We are translating the PostgreSQL documentation into Korean and operating the PostgreSQL User Group. And we are trying to contribute the PostgreSQL Global Development Group. Also, the first Korean PostgreSQL Conference will be hold in 2016. We will lead the organization of this conference. In this talk, we will present the current status of the Korean PostgreSQL User Group and the PostgreSQL DBMS market in Korea. And we also present our activities in Korea and introduce our successful migration cases of the proprietary RDBMS into PostgreSQL.

Currently, PostgreSQL uses the interpreter to execute SQL-queries. This yields an overhead caused by indirect calls to handler functions and runtime checks, which could be avoided if the query were compiled into the native code "on-the-fly" (i.e. JIT-compiled): at a run time the specific table structure is known as well as data types used in the query. This is especially important for complex queries, which performance is CPU-bound. At the moment there are two major projects that implement JIT-compilation in PostgreSQL: a commercial database Vitesse DB and an open-source project PGStorm. The former uses LLVM JIT to achieve up to 8x speedup on selected TPC-H benchmarks, while the latter JIT-compiles the query using CUDA and executes it on GPU, which allows to speed up execution of specific query types by an order.

Our work is dedicated to adding support for SQL query JIT-compilation to PostgreSQL using LLVM compiler infrastructure. In the presentation we'll discuss how JIT-compilation can be used to speed up various stages of query execution in PostgreSQL, and the specifics of translating an SQL query into LLVM bitcode to achieve good performing native code. Also we'll present preliminary results for our JIT-compiler on TPC-H benchmark.