I have a table called "nodes" with roughly 1.7 million rows in my PostgreSQL db

=#\d nodes
            Table "public.nodes"
 Column |          Type          | Modifiers 
--------+------------------------+-----------
 id     | integer                | not null
 title  | character varying(256) | 
 score  | double precision       | 
Indexes:
    "nodes_pkey" PRIMARY KEY, btree (id)

I want to use information from that table for autocompletion of a search field, showing the user a list of the ten titles having the highest score fitting to his input. So I used this query (here searching for all titles starting with "s")

=# explain analyze select title,score from nodes where title ilike 's%' order by score desc; 
                                                      QUERY PLAN                                                       
-----------------------------------------------------------------------------------------------------------------------
 Sort  (cost=64177.92..64581.38 rows=161385 width=25) (actual time=4930.334..5047.321 rows=161264 loops=1)
   Sort Key: score
   Sort Method:  external merge  Disk: 5712kB
   ->  Seq Scan on nodes  (cost=0.00..46630.50 rows=161385 width=25) (actual time=0.611..4464.413 rows=161264 loops=1)
         Filter: ((title)::text ~~* 's%'::text)
 Total runtime: 5260.791 ms
(6 rows)

This was much to slow for using it with autocomplete. With some information from Using PostgreSQL in Web 2.0 Applications I was able to improve that with a special index

=# create index title_idx on nodes using btree(lower(title) text_pattern_ops);
=# explain analyze select title,score from nodes where lower(title) like lower('s%') order by score desc limit 10;
                                                                QUERY PLAN                                                                
------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=18122.41..18122.43 rows=10 width=25) (actual time=1324.703..1324.708 rows=10 loops=1)
   ->  Sort  (cost=18122.41..18144.60 rows=8876 width=25) (actual time=1324.700..1324.702 rows=10 loops=1)
         Sort Key: score
         Sort Method:  top-N heapsort  Memory: 17kB
         ->  Bitmap Heap Scan on nodes  (cost=243.53..17930.60 rows=8876 width=25) (actual time=96.124..1227.203 rows=161264 loops=1)
               Filter: (lower((title)::text) ~~ 's%'::text)
               ->  Bitmap Index Scan on title_idx  (cost=0.00..241.31 rows=8876 width=0) (actual time=90.059..90.059 rows=161264 loops=1)
                     Index Cond: ((lower((title)::text) ~>=~ 's'::text) AND (lower((title)::text) ~<~ 't'::text))
 Total runtime: 1325.085 ms
(9 rows)

So this gave me a speedup of factor 4. But can this be further improved? What if I want to use '%s%' instead of 's%'? Do I have any chance of getting a decent performance with PostgreSQL in that case, too? Or should I better try a different solution (Lucene?, Sphinx?) for implementing my autocomplete feature?