For anyone who is interested, CompleteableFuture was the solution I employed. I was able to literally pull down over 7MB of JSON in a fraction of the time, literally all quote data for all stock exchanges. By making each request utilize a new thread, the queries ran in parallel, so fast in fact, I had to inject a slight delay in the calls, which laughably is what consumes most of the time. I have to admit, I was of the school of thought that Node.js was certainly faster due to REPL and its non-blocking architecture. However, after taking a deeper dive into the Rabbit hole of Java's multi-threaded abyss, I would strongly caution against such claims.

@Async
public void loadPriceQuotes(String stocks) throws InterruptedException, ExecutionException {

    this.currentRecord++;
    System.out.println(this.currentRecord + " => " + this.recordCount);

    URLUtility urlUtil = new URLUtility();
    RestTemplate rt = new RestTemplate();

    CompletableFuture.supplyAsync(new Supplier<QuoteResponseWrapper>() {
        @Override
        public QuoteResponseWrapper get() {

            String url = urlUtil.getPriceURL(stocks);
            ResponseEntity<QuoteResponseWrapper> response = rt.getForEntity(url, QuoteResponseWrapper.class);

            for (Quote q: response.getBody().getQuoteResponse().getResult()) {
                SkyWalker.stockQuotes.add(q);
            }

            return response.getBody();
        }
    },executor);

    return;
}