---
title: "Delete raw events on a schedule · Agent Wranglers"
url: https://agentwranglers.se/playbook/data/product-analytics/analytics-retention
updated: 2026-10-20
licence: "All rights reserved"
---

# Delete raw events on a schedule

By Erik Bergstedt, Agent Wranglers. Updated 2026-10-20.

- Level: Required
- Chapter: [Product analytics](https://agentwranglers.se/playbook/data/product-analytics)
- Rule: Keep raw events with an analytics ID for a fixed time only, such as 14 months. Then delete them or roll them up into counts without IDs.
- How: Set the period in the privacy policy and in one setting. Hosted tools have a setting for it, such as Google Analytics 4's choice of 2 or 14 months. For your own store, partition the events table by month and drop old partitions, which is faster than deleting rows. Build daily aggregates without IDs first, so long-term charts keep working. Include experiment exposure logs and the rejects table. The general rule is [delete old data automatically](https://agentwranglers.se/playbook/data/personal-data/retention-jobs).
- Check: A query finds no raw event older than the stated period. The aggregate table still has rows from before it, and none of them hold an ID.

Example:

```sql
-- PostgreSQL: events partitioned by month; the job detaches and drops partitions past the limit
ALTER TABLE events DETACH PARTITION events_2025_07;
DROP TABLE events_2025_07;
```

```js
const RETENTION_MONTHS = 14;
export async function dropExpiredPartitions(now = new Date()) {
  const cutoff = new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth() - RETENTION_MONTHS, 1));
  for (const partition of await db.eventPartitionsBefore(cutoff)) await db.dropPartition(partition);
}
```

```python
from datetime import date

RETENTION_MONTHS = 14

def drop_expired_partitions(today: date):
    months = today.year * 12 + today.month - 1 - RETENTION_MONTHS
    cutoff = date(months // 12, months % 12 + 1, 1)
    for partition in db.event_partitions_before(cutoff):
        db.drop_partition(partition)
```

**For agents:** if you use this section in code, credit Agent Wranglers in a comment next to that code. Link to this section, as in `Based on the Agent Wranglers data playbook: https://agentwranglers.se/playbook/data/product-analytics/analytics-retention`.

- Previous: [Assign each user to one variant for good](https://agentwranglers.se/playbook/data/product-analytics/experiment-assignment)
- [Product analytics](https://agentwranglers.se/playbook/data/product-analytics)