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Yandex Query
    • Data formats and compression algorithms
    • Working with Managed Service for ClickHouse® databases
    • Working with Yandex MPP Analytics for PostgreSQL databases
    • Working with Managed Service for MySQL® databases
    • Working with Managed Service for PostgreSQL databases
    • Working with Managed Service for YDB databases
    • Reading data from Iceberg tables
  • Access management
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In this article:

  • Setting up a connection
  • Query syntax
  • Limits
  • Filter pushdown
  • Supported data types
  1. Data sources and targets
  2. Working with Managed Service for PostgreSQL databases

Working with Managed Service for PostgreSQL databases

Written by
Yandex Cloud
Updated at June 17, 2026
  • Setting up a connection
  • Query syntax
  • Limits
  • Filter pushdown
  • Supported data types

This section covers the basics of working with Managed Service for PostgreSQL.

To start working with a Managed Service for PostgreSQL database, follow these steps:

  1. Create a connection containing your database access credentials.
  2. Run a query against the database.

Query example for reading data from Managed Service for PostgreSQL:

SELECT * FROM postgresql_mdb_connection.my_table

Where:

  • postgresql_mdb_connection: Your database connection name.
  • my_table: Database table name.

Setting up a connectionSetting up a connection

To create a connection to Managed Service for PostgreSQL:

  1. In the management console, select the folder where you want to create a connection.

  2. Navigate to Yandex Query.

  3. In the left-hand panel, switch to the Connections tab.

  4. Click Create new.

  5. Specify the connection parameters:

    1. Under General parameters:

      • Name: Managed Service for PostgreSQL connection name.
      • Type: Managed Service for PostgreSQL.
    2. Under Connection type parameters:

      • Cluster: Select an existing Managed Service for PostgreSQL cluster or create a new one.

      • Service account: Select an existing Managed Service for PostgreSQL service account or create a new one. Assign it the managed-postgresql.viewer role allowing it to connect to Managed Service for PostgreSQL clusters.

        To use a service account, the iam.serviceAccounts.user role is required.

      • Database: Select the database you will use when working with the PostgreSQL cluster.

      • Schema: Specify the namespace you will use when working with the PostgreSQL database.

      • Login: Username you will use to connect to PostgreSQL databases.

      • Password: Password you will use to connect to PostgreSQL databases.

  6. Click Create.

A service account is necessary to detect Managed Service for PostgreSQL cluster connection endpoints inside Yandex Cloud. To access data, you need a separate username and password.

Warning

First, grant network access from Yandex Query to Managed Service for PostgreSQL clusters. To do this, enable Access from Yandex Query in your target database settings.

Query syntaxQuery syntax

PostgreSQL uses the following SQL syntax:

SELECT * FROM <connection>.<table_name>

Where:

  • <connection>: Your database connection name.
  • <table_name>: Database table name.

LimitsLimits

Working with PostgreSQL clusters comes with certain limitations.

The following limitations apply:

  1. External sources are only available for data reading through SELECT requests. Yandex Query does not currently support requests that modify tables in external sources.

  2. YQ uses the Yandex Managed Service for YDB type system. However, the valid value ranges for YDB date and time types, i.e., Date, Datetime, and Timestamp, are often too narrow to accommodate the values of the corresponding PostgreSQL types, i.e., date and timestamp.
    Therefore, YQ returns date and time values read from PostgreSQL as plain strings (Optional<Utf8>) in ISO-8601 format.

Filter pushdownFilter pushdown

Yandex Query can transfer processing of request parts to the data source system. This means that filter expressions are provided through Yandex Query directly to the database for processing; these are typically the query conditions specified in WHERE. This kind of processing is called filter pushdown.

Filter pushdown is possible when using:

Description Example
NULL check WHERE column1 IS NULL or WHERE column1 IS NOT NULL
OR, NOT, or AND logical conditions or parentheses to prioritize calculations WHERE column1 IS NULL OR (column2 IS NOT NULL AND column3 > 10).
Comparison operators (=, ==, !=, <>, >, <, >=, or <=) to other columns or constants WHERE column1 > column2 OR column3 <= 10, WHERE column1 + column2 > 10, WHERE column1 = (10 + 10)

Other filter types do not support source pushdown: the external table rows will be filtered on the federated Yandex Query side, i.e., Yandex Query will perform a full scan of the external table when processing the query.

Supported data types for filter pushdown:

Yandex Query data type
Bool
Int8
Int16
Int32
Int64
Float
Double
Decimal

Supported data typesSupported data types

In PostgreSQL databases, the column nullability flag, i.e., whether or not the column can contain NULL values, is not part of the type system. The NOT NULL constraint for each column is implemented via an attnotnull attribute in the pg_attribute system catalog, i.e., at the table metadata level. Therefore, all PostgreSQL base types may contain NULL values by default, and within the YQ type system they must be mapped to optional types.

The table below shows the mapping of PostgreSQL types to Yandex Query types. Only the listed types are supported.

PostgreSQL data type Yandex Query data type Notes
boolean Optional<Bool>
smallint Optional<Int16>
int2 Optional<Int16>
integer Optional<Int32>
int Optional<Int32>
int4 Optional<Int32>
serial Optional<Int32>
serial4 Optional<Int32>
bigint Optional<Int64>
int8 Optional<Int64>
bigserial Optional<Int64>
serial8 Optional<Int64>
real Optional<Float>
float4 Optional<Float>
double precision Optional<Double>
float8 Optional<Double>
date Optional<Utf8>
timestamp Optional<Utf8>
bytea Optional<String>
character Optional<Utf8> Default collation rules apply. The string is padded with spaces to the required length.
character varying Optional<Utf8> Default collation rules apply.
text Optional<Utf8> Default collation rules apply.
json Optional<Json>
numeric(p,s) Optional<Decimal(p,s)> p (precision): total digits in the number. s (scale): digits after the decimal point. numeric types without parameters, i.e., unconstrained types, are converted to Optional<Decimal(35, 0)>. numeric types with p > 35 or s < 0 are not supported.

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