Poor performance of postgresql KNN queries

Question

There are two DB machines identical in structure and configurations with the characteristics as below. The databases are also identical in structure and contents. The performance of almost 99% of queryes is better on the new machine, only on few is is drastically degraded. Trying to narrow the investigation, I finally found that only one KNN (K Nearest Neighbour) query is the actual offender. Here is the relevant info about the table "maps" (about 820k rows) :

\d maps
                     Table "maps"
   Column   |       Type        | Collation | Nullable |                       
------------+-------------------+-----------+----------
 id         | integer           |           | not null | 
 strada     | character varying |           |          | 
(...)

 the_geom   | geography         |           |          | 
 concat_all | character varying |           |          | 
(...)

Indexes:
    "pk_maps" PRIMARY KEY, btree (id), tablespace "maps_idx"
    "ggx_maps_the_geom" gist (the_geom) WITH (fillfactor='100', buffering='on'), tablespace "maps_idx"
    "ix_maps_strada" hash (strada), tablespace "maps_idx"

Tablespace: "maps_data"

In the following "EXPLAIN ANALYZE" investigation I used a 'point' for test (in reality nothing else but a long irelevant string, for the sake of lizibility just replaced by 'point' and transformed by st_buffer in 'buffer')

EXPLAIN ANALYZE
  SELECT *
  FROM maps m
  WHERE st_buffer('point'::GEOGRAPHY,100::DOUBLE PRECISION) && m.the_geom
  ORDER BY m.the_geom<->'point'::GEOGRAPHY
  LIMIT 1;

The following are the actual machine responses :

(Machine#1 : 16CPU | 64GB RAM | Linux Ubuntu 16.04.7 LTS | PostgreSQL 9.6.21)

 Limit  (cost=0.29..1.96 rows=1 width=711) (actual time=1.306..1.306 rows=1 loops=1)
   ->  Index Scan using ggx_maps_the_geom on maps m  (cost=0.29..1.96 rows=1 width=711) (actual time=1.305..1.305 rows=1 loops=1)
         Index Cond: ('buffer'::geography && the_geom)
         Order By: (the_geom <-> 'point'::geography)
 Planning time: 2.977 ms
 Execution time: 1.480 ms
(6 rows)
Time: **6.885 ms**

(Machine#2 : 16CPU | 64GB RAM | Linux Ubuntu 20.04.2 LTS | PostgreSQL 13.2)

 Limit  (cost=0.29..1.96 rows=1 width=692) (actual time=66.421..66.422 rows=1 loops=1)
   ->  Index Scan using ggx_maps_the_geom on maps m  (cost=0.29..1.96 rows=1 width=692) (actual time=66.420..66.420 rows=1 loops=1)
         Index Cond: (the_geom && 'buffer'::geography)
         Order By: (the_geom <-> 'point'::geography)
 Planning Time: 20.289 ms
 Execution Time: 66.477 ms
(6 rows)
Time: **88.116 ms** (!)

As can be seen, a drastical performance degradation on the machine#2, despite the fact that the two machines are cvasi-identical in all of the aspects, including configurations as well. Does anyone have any idea how to deal with this ? What to check to get some clues ?