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    <p>I'd be inclined to use a hash instead of SQLite to do what you want to do. A hash is optimized to test for existence without the need to keep the values in any sorted order and with no need to keep a redundant copy of the datum in an index. The hash algorithm applied to the datum yields the location where it would be stored, if it did exist; you can seek to that location and see if it's there. I don't think you'd need to keep the hash table in RAM.</p> <p>Here's how you might take a hybrid hash/SQLite approach.</p> <p>Create a SQLite table </p> <pre><code>STORE id INTEGER PRIMARY KEY BUCKET (integer, indexed) URL (text, not indexed) status </code></pre> <p>You could have three of these tables, STORE1, STORE2, and STORE3 if you want to keep them separate by status.</p> <p>Let's assume that there will be 250,000,001 distinct buckets in each store. (You can experiment with this number; make it a prime number).</p> <p>Find a hashing algorithm that takes two inputs, the URL string and 250,000,0001 and returns a number between 1 and 250,000,001. </p> <p>When you get a URL, feed it to the hashing algorithm and it will tell you which BUCKET to look in:</p> <p>Select * from STORE where BUCKET = {the value returned by your hash function}. </p> <p>Your index on the BUCKET field will quickly return the rows, and you can examine the URLs. If the current URL is not one of them, add it:</p> <pre><code>INSERT STORE(BUCKET, URL) VALUES( {your hash return value}, theURL). </code></pre> <p>SQLite will be indexing integer values, which I think will be more efficient than indexing the URL. And the URL will be stored only once. </p>
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    1. COI wanted to elaborate on this answer but not enough space, so I'll add a second answer that is a continuation.
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    2. COI think there's no real limit to answer length. It's certainly got to be in a couple KBs...
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    3. CO@Tim, I've merged your continuation answer with this one. Feel free to delete the other answer.
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