TTL

TTL for Mutable Streams works differently from Append Stream because data is row-encoded.

Mutable Streams evaluate the timestamp of each row in the historical store asynchronously during background data merge or compaction of the key space. Expired rows are automatically garbage-collected when their TTL elapses.

info

A Mutable Stream created without a TTL cannot be altered later to support TTL, and similarly, a stream with TTL cannot have TTL removed.

Retention Based on Wall Clock

In this mode, you specify the storage setting ttl_seconds with a non-zero value.

When a row is inserted, the system automatically assigns a wall-clock timestamp to it. If a row has not been updated for longer than ttl_seconds, it becomes eligible for garbage collection during background compaction.

Syntax

CREATE MUTABLE STREAM ...
SETTINGS
    ttl_seconds=<ttl-seconds>, ...

Example

CREATE MUTABLE STREAM ttl_cached(
    id string,
    name string,
    price string,
    description string,
    event_time datetime
)
PRIMARY key id
SETTINGS
    ttl_seconds = 3600;

In this example, each row is assigned a TTL of 1 hour (3600 seconds). If a row is not updated within that time window, it will be automatically removed during the next background compaction.

Retention Based on Event Timestamp

In this mode, you must specify both the storage settings ttl_seconds (a non-zero value) and ttl_column.

The specified TTL column represents the event timestamp of each row. During background compaction, the system evaluates this column to determine whether the row has expired and should be garbage-collected.

Syntax

CREATE MUTABLE STREAM ...
SETTINGS
    ttl_seconds=<ttl-seconds>,
    ttl_column=<ttl-column>, ...

Example

CREATE MUTABLE STREAM event_ttl_cached(
    id string,
    name string,
    price string,
    description string,
    event_time datetime
)
PRIMARY key id
SETTINGS
    ttl_seconds = 3600,
    ttl_column = 'event_time';

In this example, the stream is configured with a TTL of 1 hour. If now() - event_time >= 3600, the row is considered expired and will be garbage-collected during background compaction.

Controlling TTL Frequency

TTL evaluation occurs during background merge or compaction operations. You can control how frequently these compactions run by setting periodic_compaction_seconds in kvstore_options.

Example:

CREATE MUTABLE STREAM ...
SETTINGS
    ttl_seconds = <ttl-seconds>,
    ttl_column = <ttl-column>,
    kvstore_options = 'periodic_compaction_seconds=1800;';

In this example, the storage engine is configured to trigger periodic compaction every 30 minutes (1800 seconds), which indirectly determines how often expired rows are cleaned up.

Manually Triggering Compaction

Expired data is removed only during background compaction. If you want to accelerate TTL cleanup, you can manually trigger compaction using the OPTIMIZE command.

OPTIMIZE STREAM <db.stream-name>;

This command initiates an immediate, unscheduled merge or compaction for the specified stream, helping reclaim space and remove expired rows sooner.