Is Athena Iceberg is ~10 slower comparing to usual external table?

We have time series data. And we always need only the last item for certain ID. When data is collected we usually extracting a single record by it's ID.
We have about 5*10^8 records per day in ~1K batches. Monthly size of data is ~100TB compressed. I was thought that Iceberg will be a perfect candidate if we will use MERGE INTO for each new portion of data.

However, after basic benchmark I figured out that Iceberg is about ~10x slower than usual external table. For the sake of simplicity I minimized my benchmark as much as I can. And it seams like my assumption is correct even with 12-rows-table.

Here is the benchmark

**Iceberg **

CREATE  TABLE my_test (
   my_partition bigint,
   my_data string
) 
PARTITIONED BY (
  my_partition
)
LOCATION
    's3://my-data/iceberg'
TBLPROPERTIES ( 
    'table_type' = 'ICEBERG',
    'format'='parquet'
)


insert into my_test 
values 
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(1, 'Some data'),
(2, 'Some data'),
(2, 'Some data'),
(2, 'Some data'),
(2, 'Matching data')
-- Run time: 3.586 sec


select count(*) from my_test
-- Run time: 8.293 sec

select count(*)
from my_test
where my_partition = 2
-- Run time: 7.485 sec

select *
from my_test
where my_partition = 2 and my_data = 'Matching data'
-- Run time: 7.766 sec

**External table **

CREATE EXTERNAL TABLE my_test_non_ice (
   my_data string
) 
PARTITIONED BY (
     my_partition int
)
STORED AS PARQUET
LOCATION 's3://ma-data/parquet'


insert into my_test_non_ice 
values 
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data', 1),
( 'Some data' ,2),
( 'Some data' ,2),
( 'Some data' ,2),
( 'Matching data' ,2)
-- Run time: 1.422 sec


select count(*) from my_test_non_ice
-- Run time: 1.087 sec

select count(*)
from my_test_non_ice
where my_partition = 2
-- Run time: 1.18 sec

select *
from my_test_non_ice
where my_partition = 2 and my_data = 'Matching data'
-- Run time: 790 ms

As you can see, every single query is much faster. The last one (the most interesting for me) is x10 slower. Our goal is to extract a single record in a 3 digits milliseconds time. Is it achievable at all with Iceberg tables?

To me, counting 12 rows for 8+ seconds is a kind of strange.

Any suggestions about what I'm doing wrong will be highly appreciated.