ACTIVITY_DATE | DAILY_ACTIVE_USERS | |
|---|---|---|
1 | 2025-05-22 00:00:00.000 | 1483417 |
2 | 2025-05-23 00:00:00.000 | 1479398 |
3 | 2025-05-24 00:00:00.000 | 1579672 |
4 | 2025-05-25 00:00:00.000 | 1439194 |
5 | 2025-05-26 00:00:00.000 | 1356041 |
6 | 2025-05-27 00:00:00.000 | 1023926 |
7 | 2025-05-28 00:00:00.000 | 1250580 |
8 | 2025-05-29 00:00:00.000 | 1159599 |
9 | 2025-05-30 00:00:00.000 | 1236907 |
10 | 2025-05-31 00:00:00.000 | 1219616 |
11 | 2025-06-01 00:00:00.000 | 777143 |
12 | 2025-06-02 00:00:00.000 | 735937 |
13 | 2025-06-03 00:00:00.000 | 596032 |
14 | 2025-06-04 00:00:00.000 | 629251 |
15 | 2025-06-05 00:00:00.000 | 736997 |
16 | 2025-06-06 00:00:00.000 | 656358 |
17 | 2025-06-07 00:00:00.000 | 628153 |
18 | 2025-06-08 00:00:00.000 | 651954 |
19 | 2025-06-09 00:00:00.000 | 735002 |
20 | 2025-06-10 00:00:00.000 | 882587 |
permaryDaily active users
Updated 2025-06-21
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⌄
select
date as activity_date,
count(distinct address) as daily_active_users
from
(select
date(block_timestamp) as date,
from_address as address
from kaia.core.fact_transactions
where block_timestamp >= current_date - interval '30 days'
UNION all
select date(block_timestamp) as date, to_address as address
from kaia.core.fact_transactions
where block_timestamp >= current_date - interval '30 days'
) as all_addresses
group by activity_date
order by activity_date;
Last run: 11 days ago
23
816B
2s