ACTIVITY_DATE | DAILY_ACTIVE_USERS | |
|---|---|---|
1 | 2025-05-01 00:00:00.000 | 2856402 |
2 | 2025-05-02 00:00:00.000 | 2758071 |
3 | 2025-05-03 00:00:00.000 | 2556014 |
4 | 2025-05-04 00:00:00.000 | 2365438 |
5 | 2025-05-05 00:00:00.000 | 2117205 |
6 | 2025-05-06 00:00:00.000 | 2409145 |
7 | 2025-05-07 00:00:00.000 | 2347605 |
8 | 2025-05-08 00:00:00.000 | 2641233 |
9 | 2025-05-09 00:00:00.000 | 2771623 |
10 | 2025-05-10 00:00:00.000 | 2660378 |
11 | 2025-05-11 00:00:00.000 | 2801880 |
12 | 2025-05-12 00:00:00.000 | 2485011 |
13 | 2025-05-13 00:00:00.000 | 2123325 |
14 | 2025-05-14 00:00:00.000 | 1978172 |
15 | 2025-05-15 00:00:00.000 | 1978055 |
16 | 2025-05-16 00:00:00.000 | 2114597 |
17 | 2025-05-17 00:00:00.000 | 1753262 |
18 | 2025-05-18 00:00:00.000 | 1522579 |
19 | 2025-05-19 00:00:00.000 | 1618221 |
20 | 2025-05-20 00:00:00.000 | 1749142 |
permaryDaily active users
Updated 2025-05-31
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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: 14 days ago
31
1KB
9s