  Bitmap indexes are commonly used in databases and search engines. By
exploiting bit-level parallelism, they can significantly accelerate queries.
However, they can use much memory, and thus we might prefer compressed bitmap
indexes. Following Oracle's lead, bitmaps are often compressed using run-length
encoding (RLE). Building on prior work, we introduce the Roaring compressed
bitmap format: it uses packed arrays for compression instead of RLE. We compare
it to two high-performance RLE-based bitmap encoding techniques: WAH (Word
Aligned Hybrid compression scheme) and Concise (Compressed `n' Composable
Integer Set). On synthetic and real data, we find that Roaring bitmaps (1)
often compress significantly better (e.g., 2 times) and (2) are faster than the
compressed alternatives (up to 900 times faster for intersections). Our results
challenge the view that RLE-based bitmap compression is best.
