Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters

TL;DR

This paper introduces xor filters, a new data structure that outperforms Bloom and Cuckoo filters in speed and memory efficiency for approximate set membership queries.

Contribution

The paper presents the xor filter, a novel filter that is faster and more space-efficient than existing Bloom and Cuckoo filters, with a compact variant called xor+.

Findings

Xor filters are faster than Bloom and Cuckoo filters.

Xor filters use less memory than traditional filters.

Xor+ is a highly compact variant with competitive speed.

Abstract

The Bloom filter provides fast approximate set membership while using little memory. Engineers often use these filters to avoid slow operations such as disk or network accesses. As an alternative, a cuckoo filter may need less space than a Bloom filter and it is faster. Chazelle et al. proposed a generalization of the Bloom filter called the Bloomier filter. Dietzfelbinger and Pagh described a variation on the Bloomier filter that can be used effectively for approximate membership queries. It has never been tested empirically, to our knowledge. We review an efficient implementation of their approach, which we call the xor filter. We find that xor filters can be faster than Bloom and cuckoo filters while using less memory. We further show that a more compact version of xor filters (xor+) can use even less space than highly compact alternatives (e.g., Golomb-compressed sequences) while providing speeds competitive with Bloom filters.