PostgreSQL table Engine - ClickHouse Documentation

The PostgreSQL engine allows SELECT and INSERT queries on data stored on a remote PostgreSQL server.

Currently, only PostgreSQL versions 12 and up are supported for the table engine.

Check out our Managed Postgres service. Backed by NVMe storage that is physically co-located with compute, it delivers up to 10x faster performance for workloads that are disk-bound compared to alternatives using network-attached storage like EBS and allows you to replicate your Postgres data to ClickHouse using the Postgres CDC connector in ClickPipes.

Creating a table

CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
(
    name1 type1 [DEFAULT|MATERIALIZED|ALIAS expr1] [TTL expr1],
    name2 type2 [DEFAULT|MATERIALIZED|ALIAS expr2] [TTL expr2],
    ...
) ENGINE = PostgreSQL({host:port, database, table, user, password[, schema, [, on_conflict]] | named_collection[, option=value [,..]]})

See a detailed description of the CREATE TABLE query. The table structure can differ from the original PostgreSQL table structure:

Column names should be the same as in the original PostgreSQL table, but you can use just some of these columns and in any order.
Column types may differ from those in the original PostgreSQL table. ClickHouse tries to cast values to the ClickHouse data types.
The external_table_functions_use_nulls setting defines how to handle Nullable columns. Default value: 1. If 0, the table function does not make Nullable columns and inserts default values instead of nulls. This is also applicable for NULL values inside arrays.

Engine Parameters

host:port — PostgreSQL server address.
database — Remote database name.
table — Remote table name.
user — PostgreSQL user.
password — User password.
schema — Non-default table schema. Optional.
on_conflict — Conflict resolution strategy. Example: ON CONFLICT DO NOTHING. Optional. Note: adding this option will make insertion less efficient.

Named collections (available since version 21.11) are recommended for production environment. Here is an example:

<named_collections>
    <postgres_creds>
        <host>localhost</host>
        <port>5432</port>
        <user>postgres</user>
        <password>****</password>
        <schema>schema1</schema>
    </postgres_creds>
</named_collections>

Some parameters can be overridden by key value arguments:

SELECT * FROM postgresql(postgres_creds, table='table1');

Implementation details

SELECT queries on PostgreSQL side run as COPY (SELECT ...) TO STDOUT inside read-only PostgreSQL transaction with commit after each SELECT query. Simple WHERE clauses such as =, !=, >, >=, <, <=, and IN are executed on the PostgreSQL server. All joins, aggregations, sorting, IN [ array ] conditions and the LIMIT sampling constraint are executed in ClickHouse only after the query to PostgreSQL finishes. INSERT queries on PostgreSQL side run as COPY "table_name" (field1, field2, ... fieldN) FROM STDIN inside PostgreSQL transaction with auto-commit after each INSERT statement. PostgreSQL Array types are converted into ClickHouse arrays.

Be careful - in PostgreSQL an array data, created like a type_name[], may contain multi-dimensional arrays of different dimensions in different table rows in same column. But in ClickHouse it is only allowed to have multidimensional arrays of the same count of dimensions in all table rows in same column.

Supports multiple replicas that must be listed by |. For example:

CREATE TABLE test_replicas (id UInt32, name String) ENGINE = PostgreSQL(`postgres{2|3|4}:5432`, 'clickhouse', 'test_replicas', 'postgres', 'mysecretpassword');

Replicas priority for PostgreSQL dictionary source is supported. The bigger the number in map, the less the priority. The highest priority is 0. In the example below replica example01-1 has the highest priority:

<postgresql>
    <port>5432</port>
    <user>clickhouse</user>
    <password>qwerty</password>
    <replica>
        <host>example01-1</host>
        <priority>1</priority>
    </replica>
    <replica>
        <host>example01-2</host>
        <priority>2</priority>
    </replica>
    <db>db_name</db>
    <table>table_name</table>
    <where>id=10</where>
    <invalidate_query>SQL_QUERY</invalidate_query>
</postgresql>
</source>

Usage example

Table in PostgreSQL

postgres=# CREATE TABLE "public"."test" (
"int_id" SERIAL,
"int_nullable" INT NULL DEFAULT NULL,
"float" FLOAT NOT NULL,
"str" VARCHAR(100) NOT NULL DEFAULT '',
"float_nullable" FLOAT NULL DEFAULT NULL,
PRIMARY KEY (int_id));

CREATE TABLE

postgres=# INSERT INTO test (int_id, str, "float") VALUES (1,'test',2);
INSERT 0 1

postgresql> SELECT * FROM test;
  int_id | int_nullable | float | str  | float_nullable
 --------+--------------+-------+------+----------------
       1 |              |     2 | test |
 (1 row)

Creating Table in ClickHouse, and connecting to PostgreSQL table created above

This example uses the PostgreSQL table engine to connect the ClickHouse table to the PostgreSQL table and use both SELECT and INSERT statements to the PostgreSQL database:

CREATE TABLE default.postgresql_table
(
    `float_nullable` Nullable(Float32),
    `str` String,
    `int_id` Int32
)
ENGINE = PostgreSQL('localhost:5432', 'public', 'test', 'postgres_user', 'postgres_password');

Inserting initial data from PostgreSQL table into ClickHouse table, using a SELECT query

The postgresql table function copies the data from PostgreSQL to ClickHouse, which is often used for improving the query performance of the data by querying or performing analytics in ClickHouse rather than in PostgreSQL, or can also be used for migrating data from PostgreSQL to ClickHouse. Since we will be copying the data from PostgreSQL to ClickHouse, we will use a MergeTree table engine in ClickHouse and call it postgresql_copy:

CREATE TABLE default.postgresql_copy
(
    `float_nullable` Nullable(Float32),
    `str` String,
    `int_id` Int32
)
ENGINE = MergeTree
ORDER BY (int_id);

INSERT INTO default.postgresql_copy
SELECT * FROM postgresql('localhost:5432', 'public', 'test', 'postgres_user', 'postgres_password');

Inserting incremental data from PostgreSQL table into ClickHouse table

If then performing ongoing synchronization between the PostgreSQL table and ClickHouse table after the initial insert, you can use a WHERE clause in ClickHouse to insert only data added to PostgreSQL based on a timestamp or unique sequence ID. This would require keeping track of the max ID or timestamp previously added, such as the following:

SELECT max(`int_id`) AS maxIntID FROM default.postgresql_copy;

Then inserting values from PostgreSQL table greater than the max

INSERT INTO default.postgresql_copy
SELECT * FROM postgresql('localhost:5432', 'public', 'test', 'postges_user', 'postgres_password');
WHERE int_id > maxIntID;

Selecting data from the resulting ClickHouse table

SELECT * FROM postgresql_copy WHERE str IN ('test');

┌─float_nullable─┬─str──┬─int_id─┐
│           ᴺᵁᴸᴸ │ test │      1 │
└────────────────┴──────┴────────┘

Using non-default schema

postgres=# CREATE SCHEMA "nice.schema";

postgres=# CREATE TABLE "nice.schema"."nice.table" (a integer);

postgres=# INSERT INTO "nice.schema"."nice.table" SELECT i FROM generate_series(0, 99) as t(i)

CREATE TABLE pg_table_schema_with_dots (a UInt32)
        ENGINE PostgreSQL('localhost:5432', 'clickhouse', 'nice.table', 'postgrsql_user', 'password', 'nice.schema');

See Also

​Creating a table

​Implementation details

​Usage example

​Table in PostgreSQL

​Creating Table in ClickHouse, and connecting to PostgreSQL table created above

​Inserting initial data from PostgreSQL table into ClickHouse table, using a SELECT query

​Inserting incremental data from PostgreSQL table into ClickHouse table

​Selecting data from the resulting ClickHouse table

​Using non-default schema

​Related content

Creating a table

Implementation details

Usage example

Table in PostgreSQL

Creating Table in ClickHouse, and connecting to PostgreSQL table created above

Inserting initial data from PostgreSQL table into ClickHouse table, using a SELECT query

Inserting incremental data from PostgreSQL table into ClickHouse table

Selecting data from the resulting ClickHouse table

Using non-default schema

Related content