PostgreSQL

Page describing how to integrate Postgres with ClickHouse

A full migration guide for PostgreSQL to ClickHouse, including advice on data modeling and equivalent concepts, can be found here. The following describes how to connect ClickHouse and PostgreSQL.

Connecting ClickHouse to PostgreSQL

This page covers following options for integrating PostgreSQL with ClickHouse:

• using the PostgreSQL table engine, for reading from a PostgreSQL table
• using the experimental MaterializedPostgreSQL database engine, for syncing a database in PostgreSQL with a database in ClickHouse

Check out our Managed Postgres service. Backed by NVMe storage that is physically collocated 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.

Using the PostgreSQL table engine

The PostgreSQL table engine allows SELECT and INSERT operations on data stored on the remote PostgreSQL server from ClickHouse. This article is to illustrate basic methods of integration using one table.

1. Setting up PostgreSQL

1. In postgresql.conf, add the following entry to enable PostgreSQL to listen on the network interfaces:

listen_addresses = '*'

2. Create a user to connect from ClickHouse. For demonstration purposes, this example grants full superuser rights.

CREATE ROLE clickhouse_user SUPERUSER LOGIN PASSWORD 'ClickHouse_123';

3. Create a new database in PostgreSQL:

CREATE DATABASE db_in_psg;

4. Create a new table:

CREATE TABLE table1 (
    id         integer primary key,
    column1    varchar(10)
);

5. Let’s add a few rows for testing:

INSERT INTO table1
  (id, column1)
VALUES
  (1, 'abc'),
  (2, 'def');

6. To configure PostgreSQL to allow connections to the new database with the new user for replication, add the following entry to the pg_hba.conf file. Update the address line with either the subnet or IP address of your PostgreSQL server:

# TYPE  DATABASE        USER            ADDRESS                 METHOD
host    db_in_psg             clickhouse_user 192.168.1.0/24          password

7. Reload the pg_hba.conf configuration (adjust this command depending on your version):

/usr/pgsql-12/bin/pg_ctl reload

8. Verify the new clickhouse_user can login:

psql -U clickhouse_user -W -d db_in_psg -h <your_postgresql_host>

If you’re using this feature in ClickHouse Cloud, you may need the to allow the ClickHouse Cloud IP addresses to access your PostgreSQL instance. Check the ClickHouse Cloud Endpoints API for egress traffic details.

2. Define a Table in ClickHouse

1. Login to the clickhouse-client:

clickhouse-client --user default --password ClickHouse123!

2. Let’s create a new database:

CREATE DATABASE db_in_ch;

3. Create a table that uses the PostgreSQL:

CREATE TABLE db_in_ch.table1
(
    id UInt64,
    column1 String
)
ENGINE = PostgreSQL('postgres-host.domain.com:5432', 'db_in_psg', 'table1', 'clickhouse_user', 'ClickHouse_123');

The minimum parameters needed are:

parameter	Description	example
host:port	hostname or IP and port	postgres-host.domain.com:5432
database	PostgreSQL database name	db_in_psg
user	username to connect to postgres	clickhouse_user
password	password to connect to postgres	ClickHouse_123

View the PostgreSQL table engine doc page for a complete list of parameters.

3 Test the Integration

1. In ClickHouse, view initial rows:

SELECT * FROM db_in_ch.table1

The ClickHouse table should automatically be populated with the two rows that already existed in the table in PostgreSQL:

Query id: 34193d31-fe21-44ac-a182-36aaefbd78bf

┌─id─┬─column1─┐
│  1 │ abc     │
│  2 │ def     │
└────┴─────────┘

2. Back in PostgreSQL, add a couple of rows to the table:

INSERT INTO table1
  (id, column1)
VALUES
  (3, 'ghi'),
  (4, 'jkl');

4. Those two new rows should appear in your ClickHouse table:

SELECT * FROM db_in_ch.table1

The response should be:

Query id: 86fa2c62-d320-4e47-b564-47ebf3d5d27b

┌─id─┬─column1─┐
│  1 │ abc     │
│  2 │ def     │
│  3 │ ghi     │
│  4 │ jkl     │
└────┴─────────┘

5. Let’s see what happens when you add rows to the ClickHouse table:

INSERT INTO db_in_ch.table1
  (id, column1)
VALUES
  (5, 'mno'),
  (6, 'pqr');

6. The rows added in ClickHouse should appear in the table in PostgreSQL:

db_in_psg=# SELECT * FROM table1;
id | column1
----+---------
  1 | abc
  2 | def
  3 | ghi
  4 | jkl
  5 | mno
  6 | pqr
(6 rows)

This example demonstrated the basic integration between PostgreSQL and ClickHouse using the PostrgeSQL table engine. Check out the doc page for the PostgreSQL table engine for more features, such as specifying schemas, returning only a subset of columns, and connecting to multiple replicas. Also check out the ClickHouse and PostgreSQL - a match made in data heaven - part 1 blog.

Using the MaterializedPostgreSQL database engine

The PostgreSQL database engine uses the PostgreSQL replication features to create a replica of the database with all or a subset of schemas and tables. This article is to illustrate basic methods of integration using one database, one schema and one table.

In the following procedures, the PostgreSQL CLI (psql) and the ClickHouse CLI (clickhouse-client) are used. The PostgreSQL server is installed on linux. The following has minimum settings if the postgresql database is new test install

1. In PostgreSQL

1. In postgresql.conf, set minimum listen levels, replication wal level and replication slots:

add the following entries:

listen_addresses = '*'
max_replication_slots = 10
wal_level = logical

*ClickHouse needs minimum of logical wal level and minimum 2 replication slots

2. Using an admin account, create a user to connect from ClickHouse:

CREATE ROLE clickhouse_user SUPERUSER LOGIN PASSWORD 'ClickHouse_123';

*for demonstration purposes, full superuser rights have been granted.

3. create a new database:

CREATE DATABASE db1;

4. connect to the new database in psql:

\connect db1

5. create a new table:

CREATE TABLE table1 (
    id         integer primary key,
    column1    varchar(10)
);

6. add initial rows:

INSERT INTO table1
(id, column1)
VALUES
(1, 'abc'),
(2, 'def');

7. Configure PostgreSQL allow connections to the new database with the new user for replication. Below is the minimum entry to add to the pg_hba.conf file:

# TYPE  DATABASE        USER            ADDRESS                 METHOD
host    db1             clickhouse_user 192.168.1.0/24          password

*for demonstration purposes, this is using clear text password authentication method. update the address line with either the subnet or the address of the server per PostgreSQL documentation

8. reload the pg_hba.conf configuration with something like this (adjust for your version):

/usr/pgsql-12/bin/pg_ctl reload

9. Test the login with new clickhouse_user:

 psql -U clickhouse_user -W -d db1 -h <your_postgresql_host>

2. In ClickHouse

1. log into the ClickHouse CLI

clickhouse-client --user default --password ClickHouse123!

2. Enable the PostgreSQL experimental feature for the database engine:

SET allow_experimental_database_materialized_postgresql=1

3. Create the new database to be replicated and define the initial table:

CREATE DATABASE db1_postgres
ENGINE = MaterializedPostgreSQL('postgres-host.domain.com:5432', 'db1', 'clickhouse_user', 'ClickHouse_123')
SETTINGS materialized_postgresql_tables_list = 'table1';

minimum options:

parameter	Description	example
host:port	hostname or IP and port	postgres-host.domain.com:5432
database	PostgreSQL database name	db1
user	username to connect to postgres	clickhouse_user
password	password to connect to postgres	ClickHouse_123
settings	additional settings for the engine	materialized_postgresql_tables_list = ‘table1’

For complete guide to the PostgreSQL database engine, refer to https://clickhouse.com/docs/engines/database-engines/materialized-postgresql/#settings

4. Verify the initial table has data:

ch_env_2 :) select * from db1_postgres.table1;

SELECT *
FROM db1_postgres.table1

Query id: df2381ac-4e30-4535-b22e-8be3894aaafc

┌─id─┬─column1─┐
│  1 │ abc     │
└────┴─────────┘
┌─id─┬─column1─┐
│  2 │ def     │
└────┴─────────┘

3. Test basic replication

1. In PostgreSQL, add new rows:

INSERT INTO table1
(id, column1)
VALUES
(3, 'ghi'),
(4, 'jkl');

2. In ClickHouse, verify the new rows are visible:

ch_env_2 :) select * from db1_postgres.table1;

SELECT *
FROM db1_postgres.table1

Query id: b0729816-3917-44d3-8d1a-fed912fb59ce

┌─id─┬─column1─┐
│  1 │ abc     │
└────┴─────────┘
┌─id─┬─column1─┐
│  4 │ jkl     │
└────┴─────────┘
┌─id─┬─column1─┐
│  3 │ ghi     │
└────┴─────────┘
┌─id─┬─column1─┐
│  2 │ def     │
└────┴─────────┘

4. Summary

This integration guide focused on a simple example on how to replicate a database with a table, however, there exist more advanced options which include replicating the whole database or adding new tables and schemas to the existing replications. Although DDL commands aren’t supported for this replication, the engine can be set to detect changes and reload the tables when there are structural changes made.

For more features available for advanced options, please see the reference documentation.