Bloom Filter for 208 million URLs
Using the formula from wikipedia for Bloom filter false positives, your proposal would have a false positive probability of about 0.00726%.  This assumes, among other things, that good hash functions are used.  The formula is:

$(1 - (1 - [1/m])^{kn})^k$

where $m$ is the number of bits in the filter, $k$ is the number of hash functions and $n$ is the number of entries in the filter.

Because items cannot be removed from a typical Bloom filter, if generation of the filter is too expensive, you might consider a counting Bloom filter to allow deletions.

(Although I have not read of it being used and do not know if it would be effective, one might use ORed signatures in each field instead of a set bit, where each signature has half or fewer of the bits set.  A possible match is found when ((entry_signature ^ test_signature) &amp; test_signature) == 0 for each entry selected by a hash function.  If every signature has the same number of set bits, this would be like nesting a Bloom filter with a size equal to the signature size and the number of hash functions equal to the number of set bits.)