PgConf.Russia 2020

Many businesses which use Database management systems like Oracle, DB2 & MS SQL are unreliable these days. Moreover, the costs incurred in maintaining these systems and its product licenses keeps on increasing. As the competitors are migrating over to the new technologies and tools available in the market, it is necessary for these businesses to migrate to new environment which is efficient, consistent and reliable to stay in the market and the technologies used in the current environment have become obsolete or no longer serve the business purpose. PostgreSQL has emerged as a top open-source RDBMS software. Since there is no licensing cost associated with it most of the companies are planning to migrate the databases which are currently running on other RDBMS like Oracle, DB2, MS SQL server to PostgreSQL. This report summarizes the various methodologies, procedures and techniques involved in successfully migrating the data from Oracle to PostgreSQL & DB2 to PostgreSQL. Migration is not a simple effort there should be proper planning and testing involved in this right from database connectivity to performance analysis. In this paper we are going to cover most of the steps which we need to consider before the migration and after the migration like choosing the correct tools for implementing the migration, time taken to migrate ,data compatibility, code conversion, application connectivity to database, database configuration parameters, performance analysis, replication setups, database monitoring, patching and backup strategies.

Postgres has always had strong support for relational storage. However, there are many cases where relational storage is either inefficient or overly restrictive. This talk shows the many ways that Postgres has expanded to support non-relational storage, specifically the ability to store and index multiple values, even unrelated ones, in a single database field. Such storage allows for greater efficiency and access simplicity, and can also avoid the negatives of entity-attribute-value (eav) storage. The talk will cover many examples of multiple-value-per-field storage, including arrays, range types, geometry, full text search, xml, json, and records.

Я расскажу о том, как приспосабливал индекс GiST для решения одной частной задачи на примере поиска текстов, "похожих" на данный в большом наборе текстов. Сама по себе задача довольно узкая и в общем случае ценности не представляет. Но она простая, понятная и отлично подходит в качестве иллюстрации. Интересен подход к построениею стратегии индексирования и поиска при решении нестандартной поисковой задачи почти без программирования с использованием сильных сторон индекса GiST. Возможно, это поможет вам найти решение для каких-то других поисковых задач.

Мы хотим поделиться структурой и результатами теста (производительности и не только), в котором участвовали PostgreSQL/Citus и MongoDB для данных нашей компании. Это был весьма увлекательный процесс с неожиданными поворотами и неоднозначным результатом.