Как организовать структуру хранения атрибутов?
Вообще, рассуждать в отрыве от данных достаточно бессмысленно. Надо смотреть конкретные планы запросов и время выполнения.
Например, для статистики, которую вы приводили тут где-то (похоже, ответ уже потерли), у меня получаются вполне приемлемые результаты (на мой взгляд, не факт, что вас устроит):
Схема и данные
create table products (
	id serial primary key,
	name text not null
);

create table products_attributes (
	id serial primary key,
	attribute_id int not null,
	product_id int not null references products (id),
	value double precision
);


-- 10 млн продуктов
insert into products (name)
select 'p' || n from generate_series(1, 10000000) n;

-- в среднем по 10 аттрибутов на продукт
-- всего 20 разных аттрибутов
-- значения - случайные из 1-1000
insert into products_attributes(attribute_id, product_id, value)
select a,
       p.id,
       trunc(random() * 1000)
  from products p, generate_series(1, 20) a
 where random() < 0.5;


create index ix_attr_attribute_id on products_attributes(attribute_id);
create index ix_attr_product_id on products_attributes(product_id);
create unique index uk_attr_attr_product on products_attributes(product_id, attribute_id);
create index ix_attr_value on products_attributes(value);

-- немного статистики
select attribute_id, count(*) from products_attributes group by 1 order by 1;

 attribute_id |  count
--------------+---------
            1 | 5001345
            2 | 5001937
            3 | 4998754
            4 | 4998706
            5 | 4999357
            6 | 5004465
            7 | 4999215
...

select product_id, count(*) from products_attributes group by 1 order by 2 desc limit 20;
 product_id | count
------------+-------
    4769292 |    20
    5366802 |    20
    7241348 |    20
    3019891 |    20
    7789046 |    20
    1688646 |    19
    1585970 |    19
...

SELECT count(*) FROM products_attributes WHERE attribute_id = 1 AND value BETWEEN 1 AND 400;
  count
---------
 1999212
(1 row)

SELECT count(*) FROM products_attributes WHERE attribute_id = 2 AND value BETWEEN 1 AND 400;
  count
---------
 1999385
(1 row)

SELECT count(*) FROM products_attributes WHERE attribute_id = 3 AND value BETWEEN 20 AND 30;
 count
-------
 55318
(1 row)


explain analyze
select * from products
 where id in (
   select product_id from products_attributes
    where attribute_id = 1 AND value BETWEEN 1 AND 400
 )
 and id in (
   select product_id from products_attributes
    where attribute_id = 2 AND value BETWEEN 1 AND 400
 )
 and id in (
   select product_id from products_attributes
    where attribute_id = 3 AND value BETWEEN 20 AND 30
 );
Без лимита, 2189 записей - 3.8 сек:
План
QUERY PLAN                          
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Gather  (cost=164603.86..347381.12 rows=2047 width=12) (actual time=680.688..3753.927 rows=2189 loops=1)
   Workers Planned: 2
   Workers Launched: 2
   ->  Nested Loop  (cost=163603.86..346176.42 rows=853 width=12) (actual time=652.714..3713.617 rows=730 loops=3)
         ->  Nested Loop  (cost=163603.43..341334.66 rows=762 width=12) (actual time=652.439..3294.369 rows=730 loops=3)
               ->  Parallel Hash Join  (cost=163602.86..313081.39 rows=4167 width=8) (actual time=649.437..1742.210 rows=3689 loops=3)
                     Hash Cond: (products_attributes_1.product_id = products_attributes_2.product_id)
                     ->  Parallel Index Scan using ix_attr_attribute_id on products_attributes products_attributes_1  (cost=0.57..147444.27 rows=775173 width=4) (actual time=0.577..880.079 rows=666462 loops=3)
                           Index Cond: (attribute_id = 2)
                           Filter: ((value >= '1'::double precision) AND (value <= '400'::double precision))
                           Rows Removed by Filter: 1000851
                     ->  Parallel Hash  (cost=163306.17..163306.17 rows=23690 width=4) (actual time=647.483..647.483 rows=18439 loops=3)
                           Buckets: 65536  Batches: 1  Memory Usage: 2752kB
                           ->  Parallel Index Scan using ix_attr_attribute_id on products_attributes products_attributes_2  (cost=0.57..163306.17 rows=23690 width=4) (actual time=18.296..639.541 rows=18439 loops=3)
                                 Index Cond: (attribute_id = 3)
                                 Filter: ((value >= '20'::double precision) AND (value <= '30'::double precision))
                                 Rows Removed by Filter: 1647812
               ->  Index Scan using uk_attr_attr_product on products_attributes  (cost=0.57..6.78 rows=1 width=4) (actual time=0.420..0.420 rows=0 loops=11066)
                     Index Cond: ((product_id = products_attributes_1.product_id) AND (attribute_id = 1))
                     Filter: ((value >= '1'::double precision) AND (value <= '400'::double precision))
                     Rows Removed by Filter: 0
         ->  Index Scan using products_pkey on products  (cost=0.43..6.35 rows=1 width=12) (actual time=0.572..0.572 rows=1 loops=2189)
               Index Cond: (id = products_attributes.product_id)
 Planning Time: 4.481 ms
 JIT:
   Functions: 93
   Options: Inlining false, Optimization false, Expressions true, Deforming true
   Timing: Generation 14.220 ms, Inlining 0.000 ms, Optimization 2.852 ms, Emission 50.889 ms, Total 67.961 ms
 Execution Time: 3762.035 ms
(29 rows)


То же, но с лимитом (LIMIT 20):
Запросexplain analyze
select * from products
 where id in (
   select product_id from products_attributes
    where attribute_id = 1 AND value BETWEEN 1 AND 400
 )
 and id in (
   select product_id from products_attributes
    where attribute_id = 2 AND value BETWEEN 1 AND 400
 )
 and id in (
   select product_id from products_attributes
    where attribute_id = 3 AND value BETWEEN 20 AND 30
 ) limit 20;

20 записей - 48 мсек:
spoilerQUERY PLAN                                   
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=2.14..7292.14 rows=20 width=12) (actual time=3.743..47.724 rows=20 loops=1)
   ->  Nested Loop  (cost=2.14..746133.39 rows=2047 width=12) (actual time=3.741..47.714 rows=20 loops=1)
         ->  Nested Loop  (cost=1.70..734511.89 rows=1829 width=12) (actual time=3.313..44.710 rows=20 loops=1)
               ->  Nested Loop  (cost=1.14..666709.45 rows=10000 width=8) (actual time=2.377..42.276 rows=95 loops=1)
                     ->  Index Scan using ix_attr_attribute_id on products_attributes products_attributes_2  (cost=0.57..209246.27 rows=56856 width=4) (actual time=1.250..14.969 rows=511 loops=1)
                           Index Cond: (attribute_id = 3)
                           Filter: ((value >= '20'::double precision) AND (value <= '30'::double precision))
                           Rows Removed by Filter: 46859
                     ->  Index Scan using uk_attr_attr_product on products_attributes products_attributes_1  (cost=0.57..8.05 rows=1 width=4) (actual time=0.053..0.053 rows=0 loops=511)
                           Index Cond: ((product_id = products_attributes_2.product_id) AND (attribute_id = 2))
                           Filter: ((value >= '1'::double precision) AND (value <= '400'::double precision))
                           Rows Removed by Filter: 0
               ->  Index Scan using uk_attr_attr_product on products_attributes  (cost=0.57..6.78 rows=1 width=4) (actual time=0.025..0.025 rows=0 loops=95)
                     Index Cond: ((product_id = products_attributes_1.product_id) AND (attribute_id = 1))
                     Filter: ((value >= '1'::double precision) AND (value <= '400'::double precision))
                     Rows Removed by Filter: 0
         ->  Index Scan using products_pkey on products  (cost=0.43..6.35 rows=1 width=12) (actual time=0.149..0.149 rows=1 loops=20)
               Index Cond: (id = products_attributes.product_id)
 Planning Time: 9.959 ms
 Execution Time: 47.796 ms
(20 rows)

Как видите, оценки планировщика по селективности адекватные. Начинает он с самого высоко-селективного условия. Лимит проносится внутрь самых глубоких джойнов (видно по количеству записей).
Мое решение по итогу:
Использование атрибутов трех типов
int (и date сюда же)
float 
string (сюда же идентификаторы из других таблиц, обеспечение ссылочной целостности на уровне приложения )

CREATE TABLE "public"."products_attributes" (
    "id" int8 NOT NULL DEFAULT unique_rowid(),
    "product_id" int8 NOT NULL,
    "attribute_id" int8 NOT NULL,
    "value_int" int8,
    "value_float" numeric,
    "value_string" text,
    PRIMARY KEY ("id")
);

--- 

SELECT
  "products"."id"
FROM
  "products"

  INNER JOIN products_attributes t1 ON products.id = products_attributes.product_id 
  INNER JOIN products_attributes t2 ON products.id = products_attributes.product_id

WHERE
 "t1"."attribute_id" = 733698711938367489 
  AND "t1"."value_string" IN ('425618460007989249') 
  AND  "t2"."attribute_id" = 733699190507405313 
  AND  "t2"."value_int" >= 2020

Индексы
BTREE attribyte_id, value_string		
BTREE attribyte_id, value_int		
BTREE attribyte_id, value_float		
BTREE product_id
BTREE product_id, attribyte_id