This chapter describes some of the planned features, that we at Memgraph are working on.

Performance Improvements

Excellent database performance is one of Memgraph's long-standing goals. We will be continually working on improving the performance. This includes:

• query compilation;

• query execution;

• core engine performance;

• algorithmic improvements (i.e. bidirectional breadth-first search);

• memory usage and

• other improvements.

Improving openCypher Support

Although we have implemented the most common features of the openCypher query language, there are other useful features we are still working on.

Functions

Memgraph's openCypher implementation supports the most useful functions, but there are more which openCypher provides. Some are related to not yet implemented features like paths, while some may use the features Memgraph already supports. Out of the remaining functions, some are more useful than others and as such they will be supported sooner.

List Comprehensions

List comprehensions are similar to the supported collect function, which generates a list out of multiple values. But unlike collect, list comprehensions offer a powerful mechanism for filtering or otherwise manipulating values which are collected into a list.

For example, getting numbers between 0 and 10 and squaring them:

RETURN [x IN range(0, 10) | x^2] AS squares

Another example, to collect :Person nodes with age less than 42, without list comprehensions can be achieved with:

MATCH (n :Person) WHERE n.age < 42 RETURN collect(n)

Using list comprehensions, the same can be done with the query:

MATCH (n :Person) RETURN [n IN collect(n) WHERE n.age < 42]