title: Alternatives to Bloom Filter
body: <p>I have tried using bloom filter for performing membership tests. I wish to perform membership tests on 80 billion entries with only allowing around 100 collisions to happen i.e., only 100 entries can be given a false positive result. </p>
  
  <p>I know this can be achieved by bloom filters but using the formulas of determining the number of bits required per entry and the number of hash functions given the allowed false positive rate. I figured I would end up using 270 GB of memory and 19 hash functions. </p>
  
  <p>I also had a look at Cuckoo filter but its memory requirements don't match my requirements. My Requirements are as follows : </p>
  
  <ol>
  <li>Use at max 6 bits per element</li>
  <li>Use no more than 7-8 Hash Functions.</li>
  </ol>
  
  <p>Could someone suggest me a probabilistic data structure other than the one's mentioned above that can help in achieving my requirements?</p>