Open Source SQL databases enters millions queries per second era
It's widespread belief that SQL DBMSes are doomed to be hulking because of burden of backward compatibility. This belief is frequently used by marketing of various NoSQL DBMSes. However, this is not necessary true. Development in Open Source community makes product development flexible enough to meet needs of the times. MySQL and PostgreSQL, which are most popular Open Source DBMSes, recently made optimizations for big servers which made it possible to process more than million of SQL queries per second in the single instance. This talk will cover particular optimizations made in PostgreSQL for achieving this result, which could previously seem like fantastic. And one may say that Open Sourcse DBMSes open a new era of millions queries per second.
Principal Technical Services Engineer, Percona
Sveta Smirnova works as MySQL Support engineer since year 2006, she is also author of book "MySQL Troubleshooting" and author of JSON UDF functions for MySQL. In years 2006 - 2015 she worked in in Bugs Analysis MySQL Support Group in MySQL AB, then Sun, then Oracle. In March 2015 Sveta joined Support Team in Percona. In years 2012-2015 she worked on bugs priority. She was also Support representative in MySQL Backup Development Team. She works on tricky support issues and MySQL software bugs on a daily basis. Before starting at MySQL in 2006, she worked as web developer on several closed CRM systems. In years 2012-2015 she worked on MySQL Labs project "JSON UDFs for MySQL". She is active participant in the open source community. Her main interests in recent years is solving DBA problems, finding ways to semi-automate this process and effective backup techniques. Sveta is author of the book "MySQL Troubleshooting" (http://shop.oreilly.com/product/0636920021964.do)
CEO of Development, Postgres Professional
PostgreSQL major contributor, developed following PostgreSQL features: CREATE ACCESS METHOD command, generic WAL interface, lockfree Pin/UnpinBuffer, index based search for regular expressions, compression and "fast scan" for GIN indexes, buffering build and better split functions for GiST indexes, statistics and selectivity estimation for range and array types, advances to fuzzy string search, lossy KNN-GiST. PhD in Computer Science based on PostgreSQL contribution.