Roaring Bitmaps

Health v2 · maintenance only

Adoption not part of the score

3918 stars · 593 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Roaring Bitmaps is a Java library providing compressed bitsets that outperform conventional compressed bitmap formats like WAH, EWAH, and Concise in both speed and compression. It is widely adopted in big data systems such as Apache Spark, Hive, Druid, Pinot, and Iceberg.

Use cases

• compress large sets of integers efficiently
• fast set operations like union and intersection on bitmaps
• build bitmap indexes for columnar databases
• reduce memory usage of bitsets in analytics engines
• serialize and memory-map compressed bitmaps
• implement inverted indexes for search

When to choose

• you need fast, memory-efficient set operations over large integer sets
• you are building analytics, search, or OLAP systems on the JVM
• you need a battle-tested library used by Spark, Druid, and Pinot
• you need serialization and memory-mapped bitmap support

When to avoid

• your integer sets are small or dense enough that plain bitsets suffice
• you need 64-bit keys without using the dedicated long-based variant
• you are not on the JVM and should use the C, Go, or Rust Roaring ports instead

Facets

library · maturity stable

serialization search-engine database databases big-data analytics performance jvm cross-platform bitset bitmap-index compression roaring-bitmaps data-structures algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="RoaringBitmap/RoaringBitmap")