If you want to get an overview on how many rows tables in your database hold one way is to count them by row intervals. This query returns number of tables by the number of their rows grouped into predefined intervals.
Query
select 
distinct
row_count_intervals,
count ("table_name") over (partition by row_count_intervals) as tables
from
(
  select t.table_schema || '.' ||  t.table_name as "table_name",
        case when t.row_count > 1000000000 then '1b rows and more'
        when t.row_count > 1000000 then '1m - 1b rows'
        when t.row_count > 1000 then '1k - 1m rows'
        when t.row_count > 100 then '100 - 1k rows'
        when t.row_count > 10 then '10 - 100 rows'
        else  '0 - 10 rows' end as row_count_intervals,
        t.row_count
  from information_schema.tables t
  where t.table_type = 'BASE TABLE'
  order by t.row_count
) y;
Columns
- row_count_intervals - predefined  row count intervals:
- 0 - 10 rows
- 10 - 100 rows
- 100 - 1k rows
- 1k - 1m rows
- 1m - 1b rows
- 1b rows and more
 
- tables - number of tables that row count falls in that interval
Rows
- One row represents one interval
- Scope of rows: all row count intervals that appear in the database
- Ordered by from smallest tables to the largest
Sample results
Here is a number of tables by row count in SNOWFLAKE_SAMPLE_DATA database aggregated into predefined intervals.

 
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                     
                                                                 
                                                             
                                                             
                                                             
                                                             
                                                                 
                                                             
                                                             
                                                                 
                                                             
                                                             
                                                             
                                                             Marcin Nagly
                                                                        Marcin Nagly
                                 Snowflake
                                                                Snowflake
                                 SQL Server
                                                                                                SQL Server
                                             Azure SQL Database
                                                                                                Azure SQL Database
                                             Oracle database
                                                                                                Oracle database
                                             Amazon Redshift
                                                                                                Amazon Redshift
                                             IBM Db2
                                                                                                IBM Db2
                                             Teradata
                                                                                                Teradata
                                             Vertica
                                                                                                Vertica
                                             PostgreSQL
                                                                                                PostgreSQL
                                             MySQL
                                                                                                MySQL
                                             MariaDB
                                                                                                MariaDB