This create provides an indexed, queryable column-based storage system.
The storage system is, fundamentally, row-based storage, where all rows have the same number of
columns. All columns are the same “type”, but given that they can be enum types, you can
effectively use differently typed values. Data is stored in a
where the outermost
BTreeMap is dynamically sized (and may be re-allocated as more rows come
in), whereas the innermost
Vec is expected to never change. The map index is an
autoincremented row identifier similar to the one used by SQLite:
What makes this crate interesting is that it also allows you to place indices on columns for
fast lookups. These indices are automatically updates whenever the dataset changes, so that
queries continue to return correct results. Indices should conform to either the
EqualityIndex trait or the
RangeIndex trait. As you would expect, the former allows
speeding up exact lookups, whereas the latter can also perform efficient range queries.
Queries are performed over the dataset by calling
find with a set of
Conditions that will
OR is currently not supported — issue multiple quieries instead. Each
Condition represents a value comparison against the value in a single column. The system
automatically picks what index to use to satisfy the query, using a heuristic based on the
expected number of rows returned for that column for each index.
- The set of match operations is currently fairly limited.
- The system currently provides an add/remove-only abstraction (i.e., no edit).