Skip to main content


Subscription is used to pull data change records for a specific table or materialized view (MV). The data from a subscription includes both the existing data in the table at the time of subscription creation and the incremental change records in the table after the subscription is created. You can use the method of creating a subscription cursor to retrieve the full data set or the incremental data set after a specified starting point.

This feature allows you to monitor all data changes without relying on external event stores like Kafka. Compared to the Kafka sink or other event store sinks, subscription requires fewer component and thus, less maintenance.

Create subscription

Use the syntax below to create subscription.

CREATE SUBSCRIPTION <subscription_name> FROM <table_or_mv_name> WITH (
retention = '<duration>'

The FROM clause must specify either a table or a materialized view (mv).

The retention parameter should be provided as a string in the format of an interval. It represents the duration for which incremental data will be retained. Any incremental data that exceeds the specified retention duration will be automatically deleted and will no longer be accessible.

Subscription cursor

A subscription cursor is a unit used to consume data from a subscription. In RisingWave, it’s a tool specifically designed to work in conjunction with a subscription, differing from the general cursor.

In RisingWave, the subscription cursor allows you to specify a specific starting point within the data of the subscription. Once the subscription cursor is created, you can use a loop to fetch and consume the data starting from that point onwards. A subscription can have multiple subscription cursors, which can be used to consume different ranges or intervals of data from the subscription.


The syntax of creating a subscription cursor is as follows:

DECLARE cursor_name SUBSCRIPTION CURSOR FOR subscription_name [since_clause];

The since_clause is used to specify the starting point for reading data. By setting this clause, you can control the range of data that is returned, allowing you to retrieve only the incremental data or data starting from a specific time or event.

If you don’t specify the since_clause, the returned data will include both the historical data up to the time of declaration and the incremental data after declaration. If you want to specify it, here are the available choices:

  1. since now()/proctime() : The returned data will include only the incremental data starting from the time of declaration.

  2. since begin() : The returned data will include the oldest incremental data available, typically starting from the beginning of the subscription's retention period.

  3. since unix_ms : Starts reading from the first time point greater than or equal to the specified unix_ms value. It's important to note that the unix_ms value should fall within the range of now() - subscription's retention and now.

Results parameters

After creating a subscription cursor, you can fetch the data by the FETCH NEXT FROM cursor_name command. Then you will see a result like below:


t1.v1 | t1.v2 | t1.v3 | t1.op | rw_timestamp
1 | 1 | 1 | 4 | 1715669376304
(1 row)

The op column in the result stands for the change operations. It has four options: op = 1 (insert), op = 2 (delete), op = 3 (update_insert), and op = 4 (update_insert). The update statement here is transformed into update_delete and update_insert operations. As for rw_timestamp, it corresponds to the Unix timestamp in milliseconds when the data was written.

Note that each time FETCH NEXT FROM cursor_name is called, it will return one row of incremental data from the subscribed table. It does not return all the incremental data at once, but requires the user to repeatedly call this statement to fetch the data.

This method is non-blocking. Even if the current table has no new incremental data, FETCH NEXT FROM cursor_name will not block, but will return an empty row. When new incremental data is generated, calling this statement again will return the latest row of data.


Let’s create a table t1 and subscribe this table, then create a cursor for this subscription.

-- Create a table and insert some data.
create table t1(v1 int, v2 int, v3 int);
insert into t1 values(1,1,1);

-- Create a subscription.
create subscription sub from t1 with (retention = '1D');

-- Create a subscription cursor.
declare cur subscription cursor for sub;

After creation, we can use the FETCH NEXT FROM cursor_name statement to fetch data from this cursor:

fetch next from cur;

v1 | v2 | v3 | op | rw_timestamp
1 | 1 | 1 | 1 |
(1 row)

Then we can update table t1 and fetch again to view the changes:

update t1 set v3 = 10 where v1 = 1;
fetch next from cur;

t1.v1 | t1.v2 | t1.v3 | t1.op | rw_timestamp
1 | 1 | 1 | 4 | 1715669376304
(1 row)

fetch next from cur;
t1.v1 | t1.v2 | t1.v3 | t1.op | rw_timestamp
1 | 1 | 10 | 3 | 1715669376304
(1 row)

We can also create another subscription cursor to specify since_clause . Let’s use since unix_ms to rebuild the cursor:

declare cur2 subscription cursor for sub since 1715669376304;
fetch next from cur2;

t1.v1 | t1.v2 | t1.v3 | t1.op | rw_timestamp
1 | 1 | 1 | 4 | 1715669376304
(1 row)

fetch next from cur2;
t1.v1 | t1.v2 | t1.v3 | t1.op | rw_timestamp
1 | 1 | 10 | 3 | 1715669376304
(1 row)

Subscribing via Postgres driver

For this feature, you only need to use the Postgres driver, and no extra dependencies are required.

Here’s an example using Python and psycopg2.

import psycopg2
import time

def main():
# Connect to the PostgreSQL database
conn = psycopg2.connect(

# Create a cursor object
cur = conn.cursor()

# Declare a cursor for the subscription
cur.execute("DECLARE cur SUBSCRIPTION CURSOR FOR sub_users;")

while True:
# Fetch the next row from the cursor
cur.execute("FETCH NEXT FROM cur;")
row = cur.fetchone()

if row is None:
# Sleep for 1 second if no row is fetched

# Replace with your event handling logic
print("Row fetched:", row)

# Close the cursor and connection

if __name__ == "__main__":

Example output:

Row fetched: (1, 'Alice', 30, 1, 1716434906890)
Row fetched: (2, 'Bob', 25, 1, 1716434909889)
Row fetched: (3, 'Charlie', 35, 1, 1716434912889)
Row fetched: (4, 'Diana', 28, 1, 1716434920889)

Exactly-once delivery

The persistent nature of subscriptions allows the subscriber to resume from a specific point in time (rw_timestamp) without data loss after a failure recovery. We also guarantee no duplicates in subscriptions, thus ensuring exactly-once delivery.

Persisting the consumption progress

To achieve exactly-once delivery, it’s required to periodically persist the timestamp in storage. We recommend using RisingWave as the store, as no extra component is needed.

First, we need to create a table for storing the progress.

CREATE TABLE IF NOT EXISTS subscription_progress (
progress BIGINT

Here's an example python code for retrieving and updating the consumption progress:

def get_last_progress(conn, sub_name):
with conn.cursor() as cur:
cur.execute("SELECT progress FROM subscription_progress WHERE sub_name = %s", (sub_name,))
result = cur.fetchone()
return result[0] if result else None

def update_progress(conn, sub_name, progress):
with conn.cursor() as cur:
INSERT INTO subscription_progress (sub_name, progress)
VALUES (%s, %s)
ON CONFLICT (sub_name) DO UPDATE SET progress = %s
""", (sub_name, progress, progress))

The client needs to retrieve the last progress during bootstrapping and periodically store the progress.

# Fetch the last progress from subscription_progress table
last_progress = get_last_progress(conn, sub_name)

with conn.cursor() as cur:
if last_progress is not None:
"DECLARE cur SUBSCRIPTION CURSOR FOR {} SINCE {}".format(sub_name, last_progress))
"DECLARE cur SUBSCRIPTION CURSOR FOR {};".format(sub_name))

while True:
cur.execute("FETCH NEXT FROM cur")
row = cur.fetchone()
last_progress = row[0] # 'rw_timestamp' is the progress indicator


if trigger_update():
update_progress(conn, sub_name, last_progress)

Use case

Potential use cases for subscriptions are as follows. If you have explored more use cases, feel free to share them with us in our Slack channel.

  • Real-time alerting/notification: Subscribers can employ sophisticated alerting rules to detect abnormal events and notify downstream applications.
  • Event-driven architectures: Develop event-driven systems that react to changes based on specific business logic, such as synchronizing data to microservices.

Help us make this doc better!

Was this page helpful?

Happy React is loading...