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| JSON Special Interest Group (JSIG) has been formed in the PostgreSQL community
Oleg Bartunov, CEO Postgres Professional and PostgreSQL Major Contributor gave a talk on JSONB performance at PGConf NYC 2021. After the presentation, EnterpriseDB’s Simon Riggs, another PostgreSQL Major Contributor proposed to create a PostgreSQL JSON workgroup (JSON Special Interest Group, JSIG). This group, consisting of several community members, will work together to enhance JSON functionality in Postgres for different use cases.
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| Postgres Pro Standard 14.1.1 has been released!
The Standard edition of Postgres Pro DBMS 14.1.1 has become available, along with new minor releases for the following versions: Std 9.6.24.1, Std 10.19.1, Std 11.14.1, Std 12.9.1 and Std 13.5.1.
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| PGConf.Russia Gathers 500+ IT Professionals at a Hybrid Online+Offline Event
25-26 October PGConf.Russia 2021 was held in a hybrid format to accommodate both online and offline participants. Postgres Professional organized this notable event for the 8th time; more than 500 people attended it virtually and in person. Software developers, database administrators, and top managers from the IT industry exchanged PostgreSQL best practices and shared their experience with the world’s most advanced open source database. Representatives of Intel, Yandex, EnterpriseDB, DBeaver Corp, Delivery Hero, and many other companies and organizations were speaking at PGConf.
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| PGConf.Online 2021 wrap-up: 57 talks, 30 international speakers, 2000+ registrants!
PGConf.Online wrapped up 10 days ago, and we want to share some important stats with you. We were glad to have welcomed 2000+ registrants this year with 700-900 of them joining us online each day! The total attendance/registration rate for all three days was near 75%, which is amazing!
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| Queries in PostgreSQL: 3. Sequential scan
In previous articles we discussed how the system plans a query execution and how it collects statistics to select the best plan. The following articles, starting with this one, will focus on what a plan actually is, what it consists of and how it is executed.
In this article, I will demonstrate how the planner calculates execution costs. I will also discuss access methods and how they affect these costs, and use the sequential scan method as an illustration. Lastly, I will talk about parallel execution in PostgreSQL, how it works and when to use it.
I will use several seemingly complicated math formulas later in the article. You don't have to memorize any of them to get to the bottom of how the planner works; they are merely there to show where I get my numbers from.
Pluggable storage engines
The PostgreSQL's approach to storing data on disk will not be optimal for every possible type of load. Thankfully, you have options. Delivering on its promise of extensibility, PostgreSQL 12 and higher supports custom table access methods (storage engines), although it ships only with the stock one, heap:
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| Queries in PostgreSQL: 2. Statistics
Despite the ongoing tragic events, we continue the series. In the last article we reviewed the stages of query execution. Before we move on to plan node operations (data access and join methods), let's discuss the bread and butter of the cost optimizer: statistics.
As usual, I use the demo database for all my examples. You can download it and follow along.
You will see a lot of execution plans here today. We will discuss how the plans work in more detail in later articles. For now just pay attention to the numbers that you see in the first line of each plan, next to the word rows. These are row number estimates, or cardinality.
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| How JSONB in PostgreSQL Helps Businesses Solve Today’s Data Challenges
How JSONB in PostgreSQL Helps Businesses Solve Today’s Data Challenges
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Working with large number of simultaneous connections almost inevitably leads to usage of connection pools. Unfortunately, present pooling solutions are very limited in access to all PostgreSQL features.
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PGLZ compression of individual values is used now in PostgreSQL. That’s good, but sometimes it’s possible to achieve significant compression only when compressing multiple values together. This is why we’re considering page-level data compression.
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pg_pathman extension had been developed by Postgres Professional several years ago. It provides the most effective way to partition tables in a database, capable of having thousands of partitions per table. Later a similar partitioning functionality had appeared in community PostgreSQL, being easier in administration, but remarkably less effective. Now we are working on the unification of both partitioning engines.
Postgres Professional
Postgres Professional is the Russian PostgreSQL company founded by Russian PostgreSQL contributors. Company has 50+ employees, among them three Major PostgreSQL Contributors.
Postgres Professional is an active member of international PostgreSQL community, developers had committed 93 patches to the latest release of PostgreSQL 10.0.
Our company had successfully performed large PostgreSQL projects including database migration projects for well-known Russian and international companies. We provide industrial PostgreSQL services: vendor technical support, migration, custom extensions and core patches development, migration-related consulting, training and certification.