I've just finished constructing a table of ~835 million rows using Google's ngram dataset, aggregated on the years in which they occurred so that each 2-,3-,4-, and 5-gram is represented by a single row in the table. Each word in each ngram also has a part of speech that I generated using TextBlob and textblob-aptagger, which is also stored in the ngram's row. This table is the only table in the database, and now that all the rows I could ever want are in the table, I don't expect to insert new rows or update existing ones ever again. At most, I may be deleting a undesired ngram from time to time, but even that shouldn't happen or at least should be kept to a minimum. All of this said, I still have yet to generate all of the indices I need, but I have a plan for that and will be doing it shortly.
My question is this: how can I optimize my database (particularly my configuration file) for periodic reads that occur together in short bursts, at the sacrifice of the speed of inserts, updates and deletes, all of which I should not be performing from here on out?
Specs (I realize these are sub-optimal, but I'm currently on a very tight budget): Amazon RDS; db.t2.micro; 1vCPU, 1GB RAM, SSD (currently 100GB--expect to go as high as 200GB once I've created the indices I need, and hopefully not higher); PostgreSQL 9.3.5-R1; the OS is UNIX-based, but some crazy custom Amazon stuffs and cannot be connected to directly, so any changes I can make are mostly limited to Postgres.
I've already done some research and set the following to 1.0 per several sources because of the SSD: random_page_cost and seq_page_cost. Does anyone disagree with this decision? I'm very open to suggestions!
Thanks in advance for any assistance.