TigerGraph compresses data in different ways, including dictionary based, snappy, variable byte compression etc. TigerGraph also supports attribute compression. Depending the operation, TigerGraph may not need data decompression before processing.
As a graph database, TigerGraph has materialized the relationships between data as edges so there is no joining required. Graph analytics focus mainly on how to traverse along the edges.
In-memory DBMS. TigerGraph also supports larger-than-memory databases under certain circumstances (e.g., when partial or most topology data are on disk).