Some IT companies say they support open source. In practice, that often boils down to using other people’s code and a bit of PR. We believe real contribution means commits to the core. And to do that consistently, we opened an engineering center not in a glossy capital business park, but in a place where fundamental science is part of the cultural DNA. Here’s why we’re building the future of systems programming in Novosibirsk Akademgorodok.

Все любят безопасность, пока не приходится её настраивать. Первая версия нашего аудита напоминала пульт управления АЭС: бесконечно гибко, но без инструкции не взлетишь. Мы признали поражение, послушали стоны администраторов и сделали «версию 2.0» — с классами событий и логикой, понятной человеку, а не только компилятору. История работы над ошибками, которая превратила «полочный» софт в рабочий инструмент.

Hitting the 4-billion-row limit in a TOAST table or running into an OidGen lock during a massive document import is a PostgreSQL admin’s nightmare. Sure, architects will tell you to push files to S3 — but real life often means keeping them inside the database. In this post, application optimization lead Alexander Popov breaks down how the standard bytea and pg_largeobject mechanisms work, where their bottlenecks hide, and how Postgres Pro Enterprise helps you get around those limits.

Throughout their careers engineers build systems that protect data and guard it against corruption. But what if the right approach is the opposite: deliberately corrupting data, generating it out of thin air, and creating forgeries indistinguishable from the real thing?

Maksim Gramin, systems analyst at Postgres Professional, explains why creating fake data is a critical skill for testing, security, and development — and how to do it properly without turning your database into a junkyard of “John Smith” entries.

Technical support comes in many shapes. Sometimes it’s "try rebooting" or "check the cable." And sometimes it’s deep engineering work you wouldn’t mind dedicating your whole life to. Which version lives inside Postgres Professional, and what’s more important in this field — people or tech? We dig into this with Kamil Karimov, Senior technical support engineer at Postgres Professional.

For businesses running 1C:Enterprise, database stability and speed aren't nice-to-haves—they're make-or-break. At Postgres Professional, we're constantly working on the DBMS core, eliminating architectural bottlenecks that show up under the heavy loads typical of 1C deployments.

We've just released Postgres Pro Enterprise 17.6 with a fresh batch of improvements specifically for 1C users.

Everyone knows great documentation makes or breaks a tech product — but few realize how much work goes into it. At Postgres Professional, the docs are written with the same discipline as the code. What’s even more impressive, all of it is done by a team of just ten people. We talked to senior technical writer Ekaterina Gololobova to see how it really works — from the first task to the final commit.

One of the open challenges in the database world is keeping a database consistent across multiple DBMS instances (nodes) that independently handle client connections. The crux of the issue is ensuring that if one node fails, the others keep running smoothly — accepting connections, committing transactions, and maintaining consistency without a hitch. Think of it like a single DBMS instance staying operational despite a faulty RAM stick or intermittent access to multiple CPU cores.

My name is Andrey Lepikhov, and I’d like to kick off a discussion about the multi-master concept in PostgreSQL: its practical value, feasibility, and the tech stack needed to make it happen. By framing the problem more narrowly, we might find a solution that’s genuinely useful for the industry.

In an era dominated by high-level abstractions and a focus on rapid development, the C programming language seems like a relic to many — an "outdated" tool with manual memory management and "dangerous" pointers. But what if these are its greatest strengths?

Maxim Orlov, a programmer at Postgres Professional with 22 years of experience, argues that C is not about quick wins and fast prototypes, but about fundamental control and a deep, philosophical understanding of how computers work. Join us for a journey from an initial frustration with Pascal to a profound appreciation for C, and learn why this "bastion of calm" is more relevant than ever.

Один запрос выполняется 100 мс, другой — меньше 1 мс. Оба делают одно и то же, но второй написан на странном, почти алхимическом SQL. В чём подвох? Первый использует OR, а второй — хитрую комбинацию AND. Этот перевод — расследование того, почему условие OR так дорого обходится вашей базе данных, и практическое руководство по тому, как проектировать схемы, чтобы избежать этой ловушки производительности.

Traditional approaches to SQL query generation often rely on instruction-tuned language models, but these can be inefficient and inaccurate. In this article, we’ll explore a new method based on reinforcement learning for model fine-tuning, which can improve both the accuracy and efficiency of SQL generation.

The “test everything” principle doesn’t improve data quality — it destroys it. Hundreds of useless alerts create noise that drowns out truly important signals, and the team stops responding to them. Google and Monzo have already moved away from this approach.

Here’s how to shift from blanket testing to targeted checks at nodes with the greatest impact radius — and why one well-placed test at the source is worth more than a hundred checks downstream.

Как вы думаете, сколько человек документирует продукты в Postgres Professional? 50? 100? А вот и нет — всего десять. Рассказываем, как команде техписателей удается управлять сотнями файлов, почему их работа — это квест, и как они успевают контрибьютить в ванильный PostgreSQL.

The myth of the magical fast=true parameter is still alive and well, but in distributed databases, another contender appears: distributed=true. Neither one will save you if you don’t rethink your schema, sharding keys, sequences, queries, and migration process. We walk through every corner with a clear-eyed approach — from choosing sharding keys and colocated tables to CDC, topologies, and foreign key constraints — showing where performance really improves, where it gets more expensive, and how to deal with it.

Migration from Oracle to vanilla PostgreSQL hits roadblocks with packages, autonomous transactions, and collections—they simply don’t exist there. We’ll break down why ora2pg stumbles, how native implementations of these mechanisms in Postgres Pro Enterprise make life easier, and how ora2pgpro translates PL/SQL semantically correctly, without hacks or crude regex.

When there’s no filter on the partitioning key, local indexes turn into a marathon across partitions. The new gbtree keeps a single catalog of keys and jumps straight to the row by primary key. In this article, we’ll show the algorithm, real numbers and limitations (primary key is mandatory, ON CONFLICT does not work) — and where this eases the pain in CRM/billing.

Всю свою карьеру инженеры строят системы, которые бережно хранят данные и защищают их от искажений. А что если мы скажем, что иногда правильнее всё делать наоборот: намеренно портить данные, генерировать их из воздуха и создавать неотличимые от настоящих подделки? Системный аналитик Postgres Professional Максим Грамин расскажет, почему создание фейковых данных — это критически важный навык для тестирования, безопасности и разработки, и как научиться делать это правильно, не превращая базу в свалку из «Иванов Ивановых».

TDE comes in many flavors — from encryption at the TAM level to full-cluster encryption and tablespace markers. We take a close look at Percona, Cybertec/EDB, Pangolin/Fujitsu, and show where you lose performance and reliability, and where you gain flexibility.

On top of that, Vasily Bernstein, Deputy head of product development, and Vladimir Abramov, senior security engineer, will share how Postgres Pro Enterprise implements key rotation without rewriting entire tables — and why AES-GCM was the clear choice.

The story of the PostgreSQL logo was shared by Oleg Bartunov, CEO of Postgres Professional, who personally witnessed these events and preserved an archive of correspondence and visual design development for the database system.

Our iconic PostgreSQL logo — our beloved “Slonik” — has come a long way. Soon, it will turn thirty! Over the years, its story has gathered plenty of myths and speculation. As a veteran of the community, I decided it’s time to set the record straight, relying on the memories of those who were there. Who actually came up with it? Why an elephant? How did it end up in a diamond, and how did the Russian word “slonik” become a part of the global IT vocabulary?

START is an open-source LLM designed for precise calculations and code verification. It addresses two major issues that most standard models face: hallucinations and errors in multi-step calculations. This article explains why these problems arise and how START solves them.