How to: Data Structures
_Efficient and specific data structures._

- [Apache Avro](https://avro.apache.org) - Data interchange format with dynamic typing, untagged data, and absence of manually assigned IDs.
- [Apache Orc](https://orc.apache.org) - Fast and efficient columnar storage format for Hadoop-based workloads.
- [Apache Parquet](https://parquet.apache.org) - Columnar storage format based on assembly algorithms from Google's paper on Dremel.
- [Apache Thrift](https://thrift.apache.org) - Data interchange format that originated at Facebook.
- [Big Queue](https://github.com/bulldog2011/bigqueue) - Fast and persistent queue based on memory-mapped files.
- [HyperMinHash-java](https://github.com/LiveRamp/HyperMinHash-java) - Probabilistic data structure for computing union, intersection, and set cardinality in loglog space.
- [Persistent Collection](https://github.com/hrldcpr/pcollections) - Persistent and immutable analogue of the Java Collections Framework.
- [Protobuf](https://github.com/protocolbuffers/protobuf) - Google's data interchange format.
- [RoaringBitmap](https://github.com/RoaringBitmap/RoaringBitmap) - Fast and efficient compressed bitmap.
- [SBE](https://github.com/real-logic/simple-binary-encoding) - Simple Binary Encoding, one of the fastest message formats around.
- [Tape](https://github.com/square/tape) - Lightning-fast, transactional, file-based FIFO.
- [Wire](https://github.com/square/wire) - Clean, lightweight protocol buffers.