ORC is a self-describing type-aware columnar file format designed
for Hadoop workloads. It is optimized for large streaming reads,
but with integrated support for finding required rows quickly.
Storing data in a columnar format lets the reader read, decompress,
and process only the values that are required for the current query.
Because ORC files are type-aware, the writer chooses the most
appropriate encoding for the type and builds an internal index as
the file is written. Predicate pushdown uses those indexes to
determine which stripes in a file need to be read for a particular
query and the row indexes can narrow the search to a particular set
of 10,000 rows. ORC supports the complete set of types in Hive,
including the complex types: structs, lists, maps, and unions.

• Alexey Shabalin