Russian Postgres Professional has updated Postgres Pro AXE — a system for analyzing large volumes of data based on PostgreSQL. In version 2.0, developers added a mechanism that allows working with analytical data via standard SQL, without special stored procedures. Now users can work with analytical data using the same SQL queries that are used for regular PostgreSQL tables.

The main change in AXE 2.0 concerns working with analytical data. Previously, accessing it required special commands and pre-prepared procedures. Now, developers have added their own Table Access Method mechanism, which allows accessing analytical data using regular SQL queries. Essentially, users no longer need separate ways to work with analytics — it can be queried much like regular tables in PostgreSQL.

In Postgres Pro AXE, analytical data is stored in Parquet format. The platform also uses a separate metadata catalog, which contains information about analytical objects and allows working with large volumes of data without having to access the content of all files every time. This architecture is already provided for in the Postgres Pro AXE documentation.

The product itself is designed for analytical workloads that require processing large volumes of information. Postgres Professional indicates support for OLAP scenarios and hybrid workloads, where transactional and analytical operations run in the same infrastructure.

The first public version of Postgres Pro AXE appeared in January 2026

It featured vectorized analytical queries, work with columnar storage and Parquet files, building data warehouses, and analyzing historical information. Version 2.0 develops the interaction of the analytical engine with PostgreSQL. The developers specifically noted the transition from special procedures to standard SQL.

As a result, Postgres Pro AXE remains a system for analytical data processing, but working with it becomes closer to the familiar PostgreSQL model, including analytical tables, queries, and access rights that can be organized in a single environment. Postgres Professional documentation also provides for managing analytical tables, columns, schemas, Parquet files, and the metadata catalog.

Which Russian DBMS are used for analyzing large volumes of data

In the Russian market, tasks similar in scenario to Postgres Pro AXE are also covered by other analytical DBMS. They overlap in purpose but are structured differently.

One such solution is Arenadata DB. This is a massively parallel analytical DBMS for corporate data warehouses, designed for complex queries on large volumes of structured and semi-structured data. According to the vendor, this refers to volumes up to tens of petabytes.

Another product is Arenadata QuickMarts. This is a clustered columnar DBMS based on ClickHouse for fast analytics on large arrays of structured data, including data marts, operational reporting, event analysis, and logs.